Hello! I'm YuHonghong


Yu Honghong-Doctor of Computer Science at Harvard University and Doctor of Business Administration

ERP Consulting, Cloud Technology, Big Data, Blockchain, Artificial Intelligence Expert

35 years of work experience

Mobile 090-8747-9395

E-mail yuhong268@gmail.com




Yu HongHong, born in 1970, graduated from Harvard UniversityPhD, currently head of CTO of NTTDATA ,and currently head of CEO of HOC Intelligent Technology, Yu HongHong CEO/GuoLong born in 1995, graduated from Cambridge UniversityPhD ,currently head of CTO of HOC Intelligent Technology .Head of Artificial Intelligence, a scholar of the Chinese Academy of Sciences Full member of JSAI Artificial Intelligence, a member of IEEE, a member of SIGIR, a member of CAAI China Artificial Intelligence Association, AAA1 International AI He is a member of the Intelligence Association, a member of the British Artificial Intelligence China, a member of the British Artificial Intelligence Association ACM, and his main research areas are ERP consulting, cloud technology, big data, blockchain, artificial intelligence experts, computer vision, multimedia technology, and machine learning. Etc.


She is a machine learning professor at Tsinghua University. Fusion with technology megatrends, cutting-edge analytical technology, government / local government, education / medical / healthcare, finance, manufacturing, logistics, communications / broadcasting, construction / real estate, electricity / gas / water, networking, pharmaceuticals Used in agriculture, retail, manufacturing, transport, sports, aerospace, advertising, IOT, ICT and other industries. Visiting professor at Harvard Business School, visiting professor at Computer Science at Tsinghua University, visiting professor at the University of Tokyo, visiting professor at the University of Tokyo, visiting professor at Osaka University, visiting professor at Kyoto University, China Science and Technology Association, Jiangsu Province Ziang Province Government Sponsored Contest Category A Wins First Prize Big Health Industry: Biomedical, Medical Devices, Smart Healthcare, Health Care, etc. Receives Category A Highest Awards. ERP blockchain cloud technology big data artificial intelligence related fields (not limited to speech processing fields including various fields of artificial intelligence) won the highest prize in patent product competition, Ali, Tencent, Huawei and other contracts And reached numerous contracts. AI x 5G face brushing has become the mainstream payment method, WYSIWYG, short video AI animation x 5G, AR VR and 3D, intelligent driving, finance, 5G telemedicine 5G AI medicine, intelligent driving intelligent business intelligent medical public security 5G Robot 5G materials, semiconductors, sports, entertainment and other technologies are our mainstream technologies, separation and purification, innovative pharmaceuticals, biotechnology, chip design, quantum dot display, multi-touch, nano-microspheres, low-carbon nanomaterials The world's key technologies for intelligent driving, smart manufacturing, robotics, and smart medical. Face and body analysis technology, SLAM and 3D vision, general and professional image recognition, robot control and sensing, large-scale video understanding and mining, image and video processing to enhance medical image analysis, artificial intelligence computing Platform, AI supercomputing platform, self-developed training framework, AI high performance storage By combining high-performance heterogeneous computing software and hardware, high-performance, Design and develop low cost, low power edge artificial intelligence chips and solutions to open up partners. For intelligent driving and AIoT, edge-to-edge AI chips can be provided with ultra-cost performance, extreme power efficiency, open tool chains, rich algorithm model samples, and comprehensive activation services. Now, the BPU (Brain Processing Unit) based on the innovative artificial intelligence-specific computing architecture is being streamed successfully. China's first edge artificial intelligence processor-a system focused on intelligent driving and a system focused on AIoT. And it has been commercialized on a large scale. Member of the Chinese Association of Artificial Intelligence, the Science Agency of the United Kingdom, and the Technical Committee of the House of Science, the UK House of Representatives (Science and Technology Committee) British Council Open Data Institute (ODI) Alan Turing Institute for Artificial Intelligence, Cambridge University, University of Edinburgh, Oxford University, London University, including EPSRC Association of Warwick University


State-of-the-art technology for AI, IoT, RPA, OCR-AI, ERP, cloud, big data, blockchain, ICT, 5G, 3D, AR, VR, iCLIP, core industrial software, core algorithms, neutrinos, government / local government Education / Medical / Healthcare, Finance, Manufacturing, Logistics, Telecommunications / Broadcasting, Construction / Real Estate, Electricity / Gas / Water, Network, Pharmaceuticals, Agriculture, Retail, Manufacturing, Transportation, Sports, Aerospace, Advertising, IOT, ICT and Other industries

IEEE, NIPS, ICML, COLT, CVPR, ICCV, ECVC, IJCAI, AAAI, UAI, KDD, SIGIR, WWW, ACL, PAMI, IJCV, JMLR, AIJ have been published more than 100 times.




Yu HongHong, born in 1970, graduated from Harvard UniversityPhD, currently head of CTO of NTTDATA ,and currently head of CEO of HOC Intelligent Technology, Yu HongHong CEO/GuoLong born in 1995, graduated from Cambridge UniversityPhD ,currently head of CTO of HOC Intelligent Technology .Head of Artificial Intelligence, a scholar of the Chinese Academy of Sciences Full member of JSAI Artificial Intelligence, a member of IEEE, a member of SIGIR, a member of CAAI China Artificial Intelligence Association, AAA1 International AI He is a member of the Intelligence Association, a member of the British Artificial Intelligence China, a member of the British Artificial Intelligence Association ACM, and his main research areas are ERP consulting, cloud technology, big data, blockchain, artificial intelligence experts, computer vision, multimedia technology, and machine learning. Etc.

ERP Consulting, Cloud Technology, Big Data, Blockchain, Artificial Intelligence Expert

35 years of work experience




Doctor of Computer Science

-Doctor of Computer Science at Harvard University

​Yu HongHong, born in 1970, graduated from Harvard UniversityPhD, currently head of CTO of NTTDATA ,and currently head of CEO of HOC Intelligent Technology, Yu HongHong CEO/GuoLong born in 1995, graduated from Cambridge UniversityPhD ,currently head of CTO of HOC Intelligent Technology .Head of Artificial Intelligence, a scholar of the Chinese Academy of Sciences Full member of JSAI Artificial Intelligence, a member of IEEE, a member of SIGIR, a member of CAAI China Artificial Intelligence Association, AAA1 International AI He is a member of the Intelligence Association, a member of the British Artificial Intelligence China, a member of the British Artificial Intelligence Association ACM, and his main research areas are ERP consulting, cloud technology, big data, blockchain, artificial intelligence experts, computer vision, multimedia technology, and machine learning. Etc.



[9]] YuHonghong, Weiqiang Wang, Wen Gao, “Object Recognition Based on Dependent Pachinko Allocation Model”, IEEE International Conference on Image Processing, San Antonio, Texas, Sept. 16-19, 2007.

[10] YuHonghong, Libo Fu, Wen Gao, “Text Segmentation in Complex Background Based on Color and Scale Information of Character Strokes,” The 7th IEEE Pacific-Rim Conference on Multimedia 2007, Hongkong, China, Dec. 11-14, 2007

[11]] YuHonghong Weiqiang Wang, Wen Gao, “A Robust Split-and-Merge Text Segmentation Approach for Images”, The 18th International Conference of Pattern Recognition, Aug. 24-26, 2006.pp.1002-1005

[12] YuHonghong Weiqiang Wang, Qingming Huang, Wen Gao “Unsupervised Texture Classification: Automatically Discover and Classify Texture Patterns”, The 18th International Conference of Pattern Recognition, Aug. 24-26, 2006.pp.433-436

[13]] YuHonghong Weiqiang Wang, Wen Gao, “A Robust Approach for Object Recognition”, The 6th IEEE Pacific-Rim Conference on Multimedia 2006, HangZhou, China, Nov.2- Nov.4, 2006, LNCS, Vol. 4261 , pp.262-269

[14]] YuHonghong, Weiqiang Wang, Qianhui Ning, “Text Detection in Images using Texture Feature from Strokes”, The 6th IEEE Pacific-Rim Conference on Multimedia 2006, HangZhou, China, Nov.2- Nov.4, 2006, LNCS , Vol. 4261 pp.295-301

[15]] YuHonghong Zheng, Weiqiang-Wang, Wen Gao, “Effective and Efficient Object-based Image Retrieval Using Visual Phrases”, ACM Multimedia 2006, October 23-27, 2006, Santa Barbara, CA., pp 77-80

[16]] YuHonghong i, Ting Liu, Weiqiang Wang, Wen Gao, “A Broadcast Model for Web Image Annotation”, The 6th IEEE Pacific-Rim Conference on Multimedia 2006, HangZhou, China, Nov.2- Nov.4, 2006 , LNCS, Vol. 4261, pp.245-251

[17]] YuHonghong, Datong Chen, Wen Gao, Jie Yang, “Modeling Background from Compressed Video”, The Second Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, in conjunction with the Tenth IEEE International Conference on Computer Vision, Oct. Beijing, 2005.

[18]] YuHonghong, Weiqiang Wang, Wen Gao, “Research on the Discrimination of Pornographic and Bikini Images,” The First IEEE International Workshop on Multimedia Information Processing and Retrieval, Irvine, California, USA, December 12-14, 2005

[19]] YuHonghong, Weiqiang Wang, Yaowen Zhan.A Robust Text segmentation Approach in Complex Background Based on Multiple Constraints.IEEE Pacific-Rim Conference on Multimedia, Jeju Island, Korea, Nov.13-16, 2005 LNCS3767: pp.594 -605

[20]] YuHonghong “A Robust Text Segmentation Algorithm in Images and Video Frames”, 1st International Conference on Universal Digital Library, 2005

[21] YuHonghong “Local Invariant Descriptor for Image Matching”, ICASSP2005, Philadelphia, PA, USA, Mar. 19-23, 2005

[22] YuHonghong “Image Matching Based on Scale invariant regions”. Advances in Multimedia Information Processing-PCM 2004: 5th Pacific Rim Conference on Multimedia, Tokyo, Japan, pp127-134, Nov.30-Dec.3, 2004. LNCS Vol. . 3331: pp.127-134,

[23]] YuHonghong “A Region Based Image Matching Method With Regularized SAR Model”. The 5th IEEE Pacific-Rim Conference on Multimedia 2004, Tokyo Waterfront City, Japan, pp263-270, Nov.30-Dec.3, 2004, LNCS , Vol. 3331: pp. 263-270

[24]] YuHonghong “A Hybrid Approach to Detect Adult Web Images”, Advances in Multimedia Information Processing-PCM 2004: 5th Pacific Rim Conference on Multimedia, Tokyo, Japan, pp609-616, Nov.30-Dec.3, 2004 LNCS , Vol. 3331

[25] YuHonghong “Skin-Color Detection Based on Adaptive Thresholds“, Third International Conference on Image and Graphics, Hong Kong, pp250-253, Dec. 2004

[26] YuHonghong, Wei Zeng, Wen Gao, Wei-Qiang Wang. “Shape-based Adult Images Detection”, Third International Conference on Image and Graphics, Hong Kong, China, pp150-153, Dec.18-20, 2004

[27]] YuHonghong “A Novel Compressed domain Shot Segmentation Algorithm on H.264 / AVC Video”, ICIP2004, October 24-27, Singapore

[28]] YuHonghong “A Fast and Robust Speech / Music Discrimination Approach”, IEEE PCM 2003, Sigpore, Dec., 2003.

[29] Qixiang Ye, Wen Gao, Weiqiang Wang, Wei Zeng, “A Robust Text Detection Algorithm in Images and Video Frames”, IEEE PCM2003, Dec, 2003

[30]] YuHonghong “Classifying Traditional Chinese Painting Images”, IEEE PCM 2003, Sigpore, Dec., 2003.

[31]] YuHonghong “A New Texture-insensitive Edge Detection Method”, IEEE PCM 2003, Sigpore, Dec., 2003.

[32]] YuHonghong “Objectionable Image Recognition System in Compression Domain”, IDEAL2003, March 21-23, 2003, Hong Kong. LNCS2690 pp.1097-1101 LNCS2690 pp.1131-1135

[33]] YuHonghong “Illumination Invariant Shot Boundary Detection”, IDEAL2003, March 21-23, 2003, Hong Kong LNCS2690 pp.1097-1101

[34]] YuHonghong “An Index Model for MPEG-2 Streams”, The Third IEEE Pacific-Rim Conference on Multimedia 2002, Dec, 16-18, 2002, Hsinchu, Taiwan.LNCS 2532: pp.271-278

[35]] YuHonghong “A Framework for Background Detection in Video”, The Third IEEE Pacific-Rim Conference on Multimedia 2002, Dec, 16-18, 2002, Hsinchu, Taiwan. LNCS 2532: pp.799-805

[36]] YuHonghong "Locating Anchor Shots in Compression Domain Based on Neural Networks" the Fifth Asian Conference on Computer Vision 2002, Jan 23-25, 2002, Melbourne, Australia.

[37]] YuHonghong "A Fast Anchor Shot Detection Algorithm on Compressed Video", The Second IEEE Pacific-Rim Conference on Multimedia 2001, Oct, 24-26,2001, Beijing, China.LNCS 2195: pp.873-878

[38]] YuHonghong "Automatic Segmentation of News Items Based on Video and Audio Features", The Second IEEE Pacific-Rim Conference on Multimedia 2001, Oct, 24-26,2001, Beijing, China. LNCS 2195: pp. 498-505

[39]] YuHonghong "Framework of Content-Based Multimedia Retrieval for Digital Library", the 12th international Conference on New Information Technology, 2001.5, Beijing, China.

[40]] YuHonghong "News Content Highlight via Fast Caption Text Detection on Compressed Video", International Conference on Intelligent Data Engineering and Automated Learning, Hong Kong, Dec. 2000. (LNCS 1983)

Research direction:

Multimedia technology, computer vision

Regular member of JSAI Artificial Intelligence Society, member of CAAI China Artificial Intelligence Society, SIGIR member Member of AAA1 International Artificial Intelligence Association, member of British Artificial Intelligence Council, member of China-Britain Artificial Intelligence Association

JSAI Artificial Intelligence Society Regular Member https://www.ai-gakkai.or.jp/

CiNii Articles: http://ci.nii.ac.jp/

CiNii Books: http://ci.nii.ac.jp/books/

CiNii Dissertations: http://ci.nii.ac.jp/d/



Grant-in-Aid for Scientific Research | Japan Society for the Promotion of Science


Grants-in-Aid for Scientific Research-Kakenhi-: MEXT


The Agency for Science and the British House of Sciences

Technical Committee (Science and Technology Committee of the lower house)

British Council on Artificial Intelligence

Open Data Institute (ODI)

Including Alan Turing Institute, Cambridge University, Edinburgh University, Oxford University, London University, Warwick University EPSRC Association

https://www.caai.cn/China Artificial Intelligence Association

Member of AAA1 International Association for Artificial Intelligence

Team management We are confident in not only the ability to manage things according to the schedule but also the ability to read the aptitude through dialogue with each member and to allocate people to the right people in the right places and control motivation. In the past, delivery has never been delayed.

As described above, the entire development team can proceed (PMO) and can also autonomously perform engineering work as SE.

Problem solving ability

The goal was to share the process from recognizing and resolving issues with stakeholders at the right time. Assuming the processes necessary to solve the problem, visualizing the person in charge of the subdivided process, due date, etc. and sharing it with the parties concerned, the ability to reliably solve the problem by the due date is acquired. Was.

Adjusting power

We respected the positions and intentions of each stakeholder and tried to understand them in advance. Considering each idea, we assumed in advance the measures to be decided as a whole project and agreed to them at meetings and other places. With respect to the coordination items, I learned the skills to negotiate after assuming who and what to check and what conclusions would be reached.


The objective was to capture the facts from various angles and to consider the best solution. In managing issues and progress, there were times when the response did not proceed as planned and unexpected troubles occurred.However, we grasped the facts accurately without any urgency, shared it with the parties concerned, and The skill to derive is acquired.

Main experience industry, main experience Job experience 35 years

IT engineers (infrastructure engineers, application engineers), including software, information processing, communications (including IT consultants), general managers, project managers (PMs) and leaders

Strength: My strength is that I can do both infrastructure infrastructure and system development.My strength is that I have consistent experience from requirement definition to development and can develop while managing. Hearing ability, current situation analysis problem extraction and solution management. ability

Main experience:

In accordance with the development strategy proposed by the Chairman of the Board, the Group's annual business plan is developed and implemented after approval. Implements the decisions of the Chair of the Board of Directors, supervises the day-to-day operation and management of the Group and signs relevant contracts, contracts, contracts and related matters on behalf of the Group within the authority delegated by the Chair; Supervise the executive and special meetings and listen to business reports. Coordinate departmental operations, check and supervise operations and management, propose corresponding business measures, ensure the achievement of annual business goals, complete technological development trends in IT environment, marketing environment, and corporate goal plan Analyze and adjust technology R & D and marketing strategies in a timely manner. Plan to take preventive and corrective actions to ensure that goals are achieved. Establish an economic accounting and monitoring system tailored to the actual situation of the company, review the company's annual financial plans, budget plans, plans and reports, supervise execution after approval, and promote corporate culture, business operations and talent Internal control rules and systems for Building development and other aspects; coordinating and processing various external relations, participating in important industry activities, creating a good external environment for the development of the group, reviewing and approving authority within the scope of approval Exercise, Participate in key investment transformations of the group for over 25 years R & D in software technology and managing large IT groups, Understand the latest technology in the IT industry, Understand the trends and directions of industry technology development, CMM software development Understanding of process and management, and knowledge of system analysis, system design, system implementation, and software system performance. Experience in research and development of large projects, experience in managing large development teams, various links and processes such as optimization and product quality control, excellent market insight, strategic decision making ability, overall Planning, project promotion and execution, team management skills. Communication and collaboration, innovation and logical analysis skills, powerful data analysis, resource integration skills, R & D process management and control skills, scheduling and control, risk management, quality management, configuration management, etc. Consciousness, professional ethics and attitude, honesty, strong sense of responsibility, high efficiency, good service awareness, good professional etiquette and temperament, ability to withstand strong pressure. According to the development of the group's products and business, prepare strategic plans and organize the direction of the company's technology development, coordinate the company's technology development management and management, formulate technology development standards and product quality management standards You. Responsible for implementing plans, managing group technical resources, organizing and addressing key technical and quality issues in the product development process, managing group technology project declarations, in-house title evaluation, innovation awards Be responsible for reviews, new product release meetings, etc.

Comprehensive management of the company's product development and project management, responsible for ERP, blockchain cloud technology, network chain technology product systems, and artificial intelligence products.

Plan the company's technology development route and new product development, and timely understand and supervise the implementation of the technology development strategic plan.

Participate in key technology project decision-making and program reviews, guide and participate in core code development, organize and resolve key technical issues in the project development process, and independently implement overall algorithm work and technical Build and guide the problem. Experience in modeling, training, optimizing, and optimizing models, familiarity with model principles, building models according to business needs, and having practical experience tuning models.

Effectively guide the technical team, oversee and guide the work of the technical department, and establish and improve various R & D specifications and processes of the company.

Develop technical talents and improve the team's overall professional skills. Technical director with more than 150 team management experience, excellent R & D process management and control skills, initiative, and big picture, deep technical background, strong code writing ability, and system analysis ability / C ++ / With distributed computing and cloud computing, Java, Python, and other mainstream architecture and design patterns, strong architecture and design experience, and in-depth research and understanding of existing technologies in the Internet of Things and artificial intelligence. Familiarity with computing-related technology theory Familiarity with database design, analysis, code creation and debugging, familiarity with large-scale database development architecture and operation, communication, logical thinking, teamwork God is strong, passionate about work. Research and development, corporate culture as an entrepreneur and co-development with companies, a full understanding of the needs of Internet products and network users, the forefront of the unknown quest spirit, the courage and ability to solve problems in unknown fields, In the project of mastering advanced technology and transforming to rapid development. Responsible for formulating the strategic development direction of the company's distribution center and planning the implementation procedure, 15 years experience in public security, government issues, transport software distribution project management, various systems, platforms and websites in the industry. Familiar with building and shipping. Full management of PMP / IMPM certified software development projects, integration of existing delivery service resources, coordinating company daily work and project management for follow-up, construction and established software projects; software Promote project landing and related work, complete assurance of the quality and approval of the project under construction, and perform excellent work in project maintenance of existing projects; check project schedule, review project overview, all software Monitoring of delivery project implementation and approval and successful completion of mentoring projects; establishing and continually optimizing customer service delivery objectives responsible for group methodology development and implementing group project execution delivery technical team Promote and develop talents, do a good job of developing talents, do a good job of building talent teams, team training, incentive evaluation, improvement team teamwork results product analysis, data analysis function, unique product evaluation

Specialty areas, core skills

(1) ERP consulting development experience 35 years, blockchain technology, cloud, big data analysis artificial intelligence experience 24 years


Broad industry experience: He has experience in consulting in a wide range of fields, from conception to implementation and operation, for a wide range of industries, including telecommunications, finance, pharmaceuticals, automotive, manufacturing, and distribution. Based on his abundant experience in business structure analysis, he excels in IT strategy formulation and execution, problem extraction and solution. 35 years of business experience: wide range of business systems in telecommunications, finance, pharmaceuticals, automobile, manufacturing, distribution, etc. 28 years of embedded control system experience: design, development, evaluation, multi-task real-time control, semiconductor PCBA circuit design technology software Development of transport control software for semiconductor manufacturing equipment Development of embedded (control) system firmware using assembler Development of in-vehicle related software Development of firmware for information home appliances Development of various OS drivers for information home appliances, control software for mounting surveillance cameras Experience in a wide range of phases in charge of design and PLC device control software: Experience from requirement definition to detailed design, development and experience in management management General IT work / planning / consultation / business design / requirement definition / design / development / maintenance Overall system design, construction, operation, etc. Proposal, requirement definition, basic design, detailed design, coding design, development / unit test, integration / comprehensive test, operation design, development languages ​​ABAP, JAVA, C, C ++, VB, VC ++, COBOL, VB.net, C # .net , Python, Ruby, PHP, OS HP-UX, Solaris, AIX, RedHat, Windows, LINUXWindows server, LINUX server, UNIX server, Vmware. Cloud AWS, Microsoft Azure Solutions, Microsoft sharepoint office365, etc. DB: Oracle, SQLServer, ORCALE, SQL, MySQL, server, security, cloud environment construction, SAPFI / CO / SD / MM / PP / BI / BO / BW / BASISBASIS consultant , SAP HANA consultant, cloud system design / construction / operation using AWS, Azure, GCP Server design / construction / operation (UNIX, Linux, Windows) Monitoring support, development of mobile application, package (SAPR / 3, SAPECC) , ASAP, ORCALE, Dynamics, Salesforce, etc.) and IT system consulting (analysis, design, implementation, development) salesfcore implementation consultant, salesfcore development Apex driga page, visual force development, Dynamics implementation consultant, ORCALE implementation consultant.

Engineers who handle everything from IoT, blockchain, AI, and robotics. The next generation of automation technology, from cars to drones to home appliances and robots, is about to bring a connected world where all information and devices are autonomously linked. Working at the KDDI Consumer Business Planning Division and KDDI Research Institute, leading a project related to “AI x IoT x blockchain” IoT = "The Five Senses" to grasp the current situation in real time

・ Blockchain = “Nerves and blood vessels” that form the basis of reliable information transmission

・ AI = "Brain" that analyzes and understands vast amounts of information and makes decisions

・ Robotics = "Body" to execute the decided action

Blockchain, large-scale systems, machine learning, game AI, 3D modeling, Experts across domains, such as simulation engineers

Toyota Motor Corporation IHI Nihon Unisys 宇宙 Fujitsu Aerospace Exploration Agency (JAXA) Japan Maritime Association RIKEN, National Institute of Advanced Industrial Science and Technology National Institute of Informatics Artificial intelligence project with Matsushita

Image processing / analysis / recognition / AI (machine learning, etc.) applied aerospace, composite material structure analysis (technology introduction support)

Design optimization (technology introduction support), robot control


Image gyro (new positioning and navigation technology)

Although it has a face recognition technology that uses the characteristics of a conventional eigenface, it does not have sufficient recognition accuracy that can be used in situations where performance has a decisive effect on the system, such as in fully automated systems. On the other hand, with the advent of Deep Learning, Facebook's Deep Face and Pyramid CNN, which are face recognition technologies with human-like recognition accuracy, have appeared. These face recognition technologies provide high recognition accuracy by enhancing the robustness against the displacement of the face position. It was hypothesized that this would allow face recognition accuracy to reach automated levels by incorporating face alignment into conventional methods.

Therefore, the causal relationship between face recognition accuracy and registration is clarified by decomposing and evaluating the mechanism of the conventional method. [Keywords] Image processing, eigenobject recognition, face recognition, principal component analysis, linear discriminant analysis

Hayabusa x 2 VSLAM technology

Collaboration with JAXA VSLAM technology will contribute to the Yasabusa 2 mission

Japan Aerospace Exploration Agency (JAXA) Third Call for Research Proposals (RFP) "Research Project (7) Research on self-position estimation and environmental mapping technology using images for exploration robots / Wide area unexplored field・ The result of the joint research with JAXA "R & D of high value-added vSLAM technology using ultra-high sensitivity multi-camera and deep learning" adopted for "Idea type" contributes to missions such as touchdown operation of Hayabusa2 Was announced from JAXA. Research and development of high value-added vSLAM technology using ultra-sensitive multi-camera and deep learning "Research on robust Visual SLAM for textureless scenes 3rd Research Proposal Call (RFP)" Research Project (7) Of the self-position estimation and environmental map creation technology using images for the purpose / vSLAM technology obtained in the following two research proposals adopted in the "Wide area unexplored field / idea type", touch-down operation of Hayabusa2 mission etc. Was reported at the Hayabusa2 reporter briefing (18/08/02). The 3D information display tool and vSLAM demonstration device (including VR) will be used to visualize the movement of Hayabusa2 in an easy-to-understand manner. The purpose of this research and development is to develop and evaluate the performance of Visual SLAM, which has the following performance and properties assuming its use in space exploration robots and similar ground environments. (Note) SLAM (Simultaneous localization and mapping) is a technology that simultaneously obtains three-dimensional information such as the position required for robot control and the surrounding terrain and structures. The ones you use are specifically called Visual SLAM.・ Can be used on natural terrain with poor texture ・ Can be processed with limited computational resources ・ Resistant against dark fields and dynamic brightness changes ・ Robust against the influence of obstacles and moving objects ・ High-performance position estimation and 3D map development In this research and development, based on the Visual SLAM technology developed by the proposer so far, it will be further developed through joint research and development by three parties (JAXA, Ivis, View Plus), and applied for deep learning. In addition to improving the performance of such software, we aim to realize value-added Visual SLAM technology by integrating hardware technologies such as the introduction of ultra-high sensitivity cameras. Contribution of Open Innovation Business (vSLAM Research) Results to Hayabusa2 Mission "Open Innovation Hub for Exploring Solar System Frontiers to Expand the Existence and Active Areas of Kinds" Third Call for Research Proposals (RFP: Request for Proposal) ) Idea type (7) Research on position estimation and environmental map creation technology using images for exploration robots / Wide area unexplored field [1] Contribution to Hayabusa2 mission

 Hayabusa2 has arrived at the asteroid Ryugu, and preparations are underway for the first touchdown scheduled for fall 2018. Through the joint research of vSLAM (Visual SLAM) with the JAXA Space Exploration Innovation Hub, using the image of Ryugu sent from Hayabusa2, reconstructing a detailed 3D model and displaying various 3D information etc. By contributing to Hayabusa2's touchdown mission, etc. [2] Ryugu's 3D model reconstruction example, based on images taken by Yabusa2 at a distance of about 40 km from Ryugu, we reconstructed a 3D model of Ryugu. Ryugu's 3D model reconstruction using vSLAM

Main technology

Mainly Bank of Japan, Bank of Mitsubishi UFJ, Sumitomo Mitsui Banking Corporation, Nomura Securities, SBI SECURITIES, AIG Life Insurance, Mizuho Bank, and other business-related projects, AWS, Azure, GCP, and other cloud services, AI / RPA, IoT system projects (NVIDIA) Toyota and SoftBank have developed self-driving technology Nvidia has manufactured expensive semiconductors used for image processing of personal computers such as GPUs. Toyota has a taxi dispatch system with AI and operation data collection for AI. SoftBank (SoftBank) SoftBank's AI and machine learning IBM Watson, MAGELLAN BLOCKS.TOYOTA (Toyota Motor), domestic company AI, self-driving car Toyota and SoftBank's large partnership New company "MONET softbank Artificial Intelligence, Big Data, IoT, Robotics, etc. Technology Artificial Neural Network etc.) Experience, integration and control System development project)

Programming Language: C C ++ C # Clojure Cobol D Erlang F # Fortran Go Haskell HTML / CSS JavaJavascript

Julia Lisp Lua Objective-C OCamlPascal Perl PHP Python2 Python3 R RubyRust

Scala Scheme SQL Swift TypeScriptVisual Basic Kotlin

Development environment: Linux UNIX Mac OS Windows Windows Server Apache Nginx IIS Amazon Web Service Microsoft Azure Google Cloud Platform VimEmacs Eclipse Visual Studio Visual Studio CodeHadoop Redis memcached Elasticsearch ChefPuppet Ansible Terraform

Git CVS MercurialSubversion

Framework: Struts JSF Spring Play Framework CakePHPSymfony Laravel Zend Framework CodeIgniterFuelPHP Ruby on Rails

 Django Node.js jQueryAngularJS React Bootstrap Echo iris GinGoji Revel Unity Unreal Engine cocos2d.NET Framework

DirectX OpenGL iOS SDKAndroidSDK


Field of experience: Web development (server side) Web development (front end) iPhone application development Android application development Feature phone application development R & D

Consumer game development Desktop application development OS / middleware development control embedded system development General-purpose system development, data analysis ... BigData, BI

State-of-the-art specialists such as AI and IoT that collect, integrate, analyze, and reuse large amounts of accumulated data

Development environment Azure, AWS, GCP, Middle / Hadoop * Knowledge of big data, management, Tagetik, etc.

Platform / Tableau development style / Agile development, Python, Tableau, Hive / Hadoop / R language / bigdate / management, etc. For example, decision tree, neural network, regression analysis, principal component analysis (PCA) to extract features and patterns, Cluster analysis, genetic algorithm, reinforcement learning, etc.

The world's best in the industry, new technologies such as AI, machine learning, big data, IoT, BI, RPA, etc. have been used in industries such as finance, web, pharmaceutical, agriculture, retail, manufacturing, sports, etc.

AI x medical research

Medical software developed using MR (Mixed Reality) and VR (Virtual Reality) devices. Medical care in the world will certainly achieve "automation" and "unmanned".

Riding the wave of the coming medical revolution, we will make medical treatments fun and enjoyable. We create a world with a lifetime of 100 years or more with advanced technology and content capabilities, creating medical care

With the motto of "Make medical treatment fun!" And "Medical care x IT = Entertainment", we will make the revolutionary and fun change of medical care anyway, especially VR, and make use of animation and game contents to make patients happy. Giving is our mission. In order to sublimate medical care, to unmanned medical care, and to entertain medical care (entertainment), we want to make medical care interesting! The latest technology and know-how in the world's highest environment such as New York University and Harvard University. Learn. Through his experience, "Introducing the world's advanced medical technology more into Japan Dental Group We have built an environment in which dentists can learn the world's advanced medical technology and a platform for transmitting advanced medical technology in Japan.

Education business for dental professionals,

Promote home healthcare in response to an aging society,

Overseas base global expansion ...

Through the challenge of creating new business models and value creation, we opened up the potential of medical care, realized high-quality medical care, revitalized the medical industry, and contributed to society.


AI x transportation system

Research and development of technologies related to autonomous driving and connected cars. Conducts joint research with Toyota.

AI x manufacturing

Application to robotics and machine tools. Research and development of object recognition / control / abnormality detection / optimization technology. Joint research with FANUC and Hitachi.

AI x Biohealthcare

Analysis of medical images, research and development of early cancer diagnosis technology using blood. Joint research with the National Cancer Center and others from December 2017.

AI x manufacturing (robotics, optimization)

AI x traffic

AI x Biohealthcare

AI x communication

AI x machine learning

AI x simulation

AI x edge device

AI x Network

AI x high performance computing

AI x product development (general)

AI x product development (visual inspection solution)

AI x human computer / robot interaction (HCI, HRI)

AI x project case

AI x medical research

Japan's Takeda Pharmaceutical, Fujifilm, Yanyay Pharmaceutical and Others Promote New Drug Development Project with Artificial Intelligence (AI)

Medical DNA cell IPS artificial intelligence project-major hospitals in the United States, including Osaka Hospital

IBM Watson Artificial Intelligence Project

By engaging in the development of artificial intelligence, smart sensors, telescopes, detectors, and medical equipment, artificial intelligence makes our language the window of mental health and advanced image sensors enable humans to create supervision . All medical testing systems are integrated on a single computer chip, and smart sensors detect environmental pollution at the speed of light.

Based on the optimistic view of healthcare, IBM will focus on smart healthcare and achieve three key goals in the coming years. 1. Chips for diagnosing potentially fatal diseases faster than state-of-the-art laboratories. The camera observes the pill to see if its molecular structure matches the properties of the usual drug; 3. helps the system determine if the subject is suffering from mental illness.

Famous case (AI)

AI x Intel Artificial Intelligence Project

Intel facilitates open source efforts through optimized machine learning frameworks and libraries, and works with machine learning experts on Nervana systems.

Google Artificial Intelligence Project

Artificial intelligence development for language translation, visual processing, and ranking and prediction functions

AI Case Salesforce Artificial Intelligence Project Team

Salesforce uses artificial intelligence to help employees perform tasks more efficiently and streamline and accelerate productivity.

AI case Amazon Amazon ALexa artificial intelligence project and init artificial intelligence project

Developed by Amazon's artificial intelligence service robot Alexa and participating in in-depth learning of the basic AWS cloud platform The Amazon Sagemaker framework has been applied to financial software US INTUIT


Ant project artificial intelligence chip software development

Nippon Aeon Group AI Project

Financial credit loan AI prevents fraud, repayment reminder AI system

Nomura Securities Industry Consumer Finance Score Artificial Intelligence Project

He is familiar with JVM in product architecture design and has experience in JVM tuning and performance optimization.

Supermarket anti-theft AI detection system

Face recognition AI of Japanese police station arrests prisoner system

Japan's AI transportation system

Sports training AI system

VR / AR system

HCI, HRI system

Manufacturing IOT system

Visual inspection solution

3D game AI product, Preferred Networks R & D, PaintsChainer project

Omron Artificial Intelligence Cooperation

Development, operation, and improvement of new functions of the company-wide core business system (Salesforce)

・ Recommendation and search function optimization using artificial intelligence / machine learning technology (Tensorflow, etc.)

・ Development, operation, and improvement of new functions of the company-wide CRM system

・ Draft a transition strategy to the business flow that should be and promote the transition

We have developed a job recruitment automatic recommendation function using AI (machine learning) and a job seeker's intention degree automatic judgment function.・ I gained experience in consulting work, including not only a series of upstream and downstream processes of in-house system development, but also proposals for business flow improvement in the business divisions.

3D design concept art production / design

3D CG design of character modeling and texture creation, bone setup

3D CG design for background modeling and texture creation

Various motion designs using 3D CG

Composite work using AfterEffects

Character model

Background model / rigging

3D graphic design and asset production such as motion

Effect design including special effects and environmental effects

Create various interfaces such as GUI, font and logo

Technical artists such as technical development for efficient development procedures

Work experience of 3D CG using Maya or 3dsMAX

 Motion production and practical experience using any of Maya, 3dsMAX or MotionBuilder

Development experience as a technical designer

Tool development experience using scripts of each software

Interface work experience in game production

 Graphic design through DTP, WEB, etc.

Hand-drawn effect (2D) creation skills

Expert knowledge and technology such as programming languages ​​for shaders in general

Project case

It was also possible to analyze using “BigQuery” tool of “App development”, “Infrastructure operation and maintenance”, “Data analysis”, “SRE” GCP.

Realizing Big Data Use of OMRON Healthcare with GCP

Omron Healthcare is a leading company in healthcare equipment and services. As the amount of data handled in the medical industry is increasing due to the development of IoT, the use of GCP is proposed to enable more accurate data analysis and utilization. Supporting the provision of services that lead to the improvement of people's health through support for introduction and selection of optimal resources

* In addition to GCP tools, tools such as Swagger, Postman, Terraform, Ansible were used

* For development experience, languages ​​that can be used in GCP such as Java, Python, NodeJS, Ruby, Go, .NET, PHP. For experience of GCP infrastructure engineer, experience in server operation and monitoring

AI / IoT technology from the viewpoint of privacy and security

Privacy, security issues and impacts related to AI and IoT About various guidelines about AI / IoT

 Privacy and security measures to make good use of AI and IoT

Women's professional baseball organization: Women's professional baseball navigator (in charge of API and application)


(2) Deep learning R & D experience of machine learning and artificial intelligence technology 24 years

Experience in developing artificial intelligence and intelligence development environment Experience in big data acquisition and analysis Use of empirical analysis algorithms in artificial intelligence algorithm development languages ​​such as Python and TensorFlow Regression: logistic regression, SVM tree: decision tree, random forest Bayes: simple Bayes (Naive Bayes Ensemble Learning: Boostin Time Series: AR, MA, (S) ARIMA Model etc. Product Analysis: Association Analysis, ABC Analysis, Basket Analysis Business Analysis Customer Analysis: Decyl Analysis, R Natural Language Analysis: Text Analysis, Shared Kinematic network, analysis, Word 2 Vect clustering: k-nearest neighbor (KNN), hierarchical clustering, non-hierarchical clustering (K-Means), topic model / abnormality detection (outlier detection) Neural network: CNN, RNN, LSTM, Development related to Deep Learning / AI such as self-organizing map (SOM) [Artificial Intelligence (AI) / Mechanics Learning / Deep Learning] More than 10 years of experience Image authentication / face recognition (intelligent monitoring system) Python, Tensorflow (software library), C ++, Node.JS YOLO (real-time object recognition), Darknet (neural network environment) Raspberry Pi, GPU (Computing device), Arduino (AVR microcomputer) OpenCV (Image processing library), Docker (Virtualization) ROS (Robot Operationg System), Anaconda (Package for data science) R, Jupyter (Data analysis tool) MobileNet (MobileNeural network for mobile applications) Speech recognition (Functional research of Android applications) Python, htk (HMM learning tool for voice), Julius (Speech recognition engine) sequitur g2p (Cryptographic phoneme conversion) Artificial intelligence, Machine learning, Natural language processing In-depth knowledge of information retrieval game AI Experience in C / C ++ work Experience in game development on any of PlayStation3, PlayStation4, Xbox 360, Xbox One Experience in game AI system Knowledge on pathfinding / navigation mesh Knowledge of behavior tree Experience of tool development on Windows AI / IOT Artificial intelligence I am engaged in the introduction of cutting-edge technologies such as AI and RPA RPA: WinActor Hadoop, Python, NoSQL Database, Apache Spark, SQL server, Oracle Experience BI, machine learning, Data Lake hardware for data analysis and data collection terminals using machine learning such as deep learning , Production / model creation, AI platform construction, data streaming processing, front-end development [data analysis platform] Python / R / HHVM (PHP) R, Django, Ruby macro (VBA) creation, works with Raspberry Pi, Use python to create programs Use MATLAB to create programs Use SQL (PostgreSQL) (big data, AI, IoT, BI construction, analysis, etc., Hadoop, Python, NoSQL Database, Apache Spark, SQL server, Oracle, AI, IoT, security Development of AI to be installed in home appliances and drones, development experience of full-stack Web services, knowledge of Python (WSGI, numpy, async), AWS, javascript framework, etc., agile, test driven development experience, leader experience, Knowledge of digital marketing ecosystem and technology, basic knowledge of machine learning and statistics, creative software design skills using the latest technology, R, Diango, Ruby Experience in program construction / analysis, machine learning framework, statistical knowledge, development and operation of infrastructure for analyzing large-scale data, development and operation of services linked with the system Linkage of machine learning systems with data scientists Experience in development and operation, development of infrastructure supporting large-scale data such as ad networks, experience in building and operating DMP, experience in prototype development of new products System development on Linux / UNIX, handling large data sets Experience, development and operation experience of service infrastructure using cloud such as AWS and GCP, experience using distributed computing such as Hadoop / Hive System development on Linux / UNIX, experience dealing with large data sets, Experience in development and operation of service infrastructure using cloud such as AWS and GCP, distributed computing such as Hadoop / Hive Experience using, IoT, AI, autonomous driving, blockchain, GNSS… Natural language processing engineer / Data engineer / Machine learning engineer Linear regression with variable / linear algebra review Linear regression with multiple variables / Octave ・ Matlab tutorial Logistic regression / normal Neural Network: Representation Neural Network: Advice for Applying Learning Machine Learning / Machine Learning System Design Support Vector Machine (SVM) Unsupervised Learning / Dimension Reduction Anomaly Detection / Recommender System Large-scale Machine Learning Application Data Platform Area Development and operation of data platform [Data platform engineer] In charge of development and operation of platform applications that support the data use process [DevOps engineer] Operate middleware such as Hadoop, Kafka, Storm, Cassandra, Presto, MySQL, Oracle, Teradata, and improve the operation process [Middleware development engineer] In charge of OSS middleware development such as Hadoop, Kafka, Storm, Cassandra, Presto, etc. System construction, modeling, and data analysis to promote the utilization of multi-big data (hereinafter, data) in the science area [Data utilization system construction] Responsible for building a system to deliver optimal content to users based on data [Machine learning] Build a model that performs optimal distribution from huge log data by machine learning [Information search] Yahoo ! Shopping, Yahoo auctions, advertising distribution, etc. OSS-based search engine used in OSS [Natural language processing, voice processing, image processing] The latest technology for natural language processing, voice processing, image processing is turned into a tool and applied to services [large-scale data processing] Hadoop, Spark, etc. Build a large-scale data processing system that processes logs and other data using the system. In charge of creating systems and mechanisms to promote the utilization of multi-big data (hereinafter, data) with a data service area [Data Engineer] company-wide Responsible for the development and operation of data collection, cleansing, conversion, and storage for utilization [Front-end engineer] Responsible for the front-end development of a system that visualizes, analyzes, and manages data [Data warehouse engineer] Combines various data To create an environment that allows users to analyze their behavior with free ideas [Data Architect Responsible for designing data management to handle data effectively and safely [Data business] In charge of creating a system to promote the utilization of data and to spread it not only in the company but also throughout Japan As a corporate R & D domain R & D You will be in charge of technical development and on-site deployment in line with service needs. AI system development, AWS, Azure, cloud platform design / construction / operation using GCP, embedded / control system development (C / C ++ etc.), cloud service / AI / RPA system.

Experience in analysis / research using multivariate analysis, data mining, and machine learning

Experience in analysis using statistical analysis tools such as R, SPSS, SAS, etc.

Experience programming with machine learning libraries such as Python and R


Experience in Bayesian statistical modeling [Artificial Intelligence (AI) / Machine Learning / Deep Learning] Over 24 years experience

For about 13 years at NTT Data Research and Development Center and Hitachi, worked as a development center member of machine translation software "The Translation", and developed major functional parts using development languages ​​such as C and C ++. Recognized for his contribution to the industry, he received the 2009 AAAMT (Asia-Pacific Association for Machine Translation) Nagao Award.

Cooperation with other companies (Microsoft, Adobe, etc.), joint research with venture companies based in Spain, Japan Translation Federation, Technical Communicator Association, University Actively expanded outside through lectures at The company has been conducting activities not only to develop general-purpose products, but also to revitalize the entire industry.

Management in R & D of artificial intelligence technologies (text mining and data mining technologies) New business strategies and planning for R & D of power and social systems, promotion of IoT and AI

Research and development Research and development of computer vision, multimedia technology, natural language processing technology

For about 13 years from 2006 to the present, as a group leader in text and data mining, he has led 53 subordinates and has been promoting projects to improve productivity and lead time using artificial intelligence technology. In the first half of 2017, he will be in charge of a research and development budget of about 100 million yen and management of a total of 160 people (area leader). Recent projects include:

Increased yield at Yokkaichi Plant, a central base in the TOSHIBA memory business with sales of approximately ¥ 750 billion in FY2016. The world's largest Yokkaichi factory, with hundreds of processes and thousands of units, has enormous big data due to mass production. Real issues are grasped by going into the field and proceeding with discussions. By analyzing big data in cooperation with on-site staff, the company has monitored the occurrence of defects and analyzed the causes to improve the yield. We improved the efficiency of failure analysis by 50%. 2016 business award for contribution to business results.

Increased production efficiency and shortened lead time at the Keihin Plant, a production base in the thermal, hydro and nuclear businesses with sales of about 1 trillion yen in FY16. At the Keihin Plant, nonconformities caused by design at the manufacturing and product stages are accumulated. These have been effectively utilized by text mining technology to reduce nonconformity at the design stage, thereby reducing expenses. In particular, attending a design review meeting and observing behavior to understand issues at the site. In the second half of 2016, a new support function based on this was developed and integrated into the Keihin Works overall system.

Participated in the nuclear PLCM (Plant Life Cycle Management) project. Considering the use of machine learning techniques to shorten the period of periodic inspections, which has a large contribution to improving the profits of electric power companies over their lifetime. Engaged in benchmarking competitors and developing strategies that leverage their strengths.

Improve added value by analyzing TV viewing data. We analyze data per second obtained from TV and propose an analysis method for viewing patterns that were not recognized until now. He has worked on customer co-creation activities aimed at improving and optimizing the value of program production, commercials, and other promotional activities at web advertising companies and TV companies.

Analyze using “BigQuery” tool of “App development”, “Infrastructure operation and maintenance”, “Data analysis”, “SRE” GCP.

★ Realize big data utilization of OMRON Healthcare with GCP

Omron Healthcare is a leading company in healthcare equipment and services. As the amount of data handled in the medical industry is increasing due to the development of IoT, the use of GCP is proposed to enable more accurate data analysis and utilization. Through the introduction support and selection of optimal resources, we support the provision of services that lead to the improvement of people's health.

* In addition to GCP tools, use tools such as Swagger, Postman, Terraform, and Ansible.

* For development experience, languages ​​that can be used in GCP such as Java, Python, NodeJS, Ruby, Go, .NET, PHP. For experience of GCP infrastructure engineer, experience in server operation and monitoring

Thinking about AI / IoT technology from the viewpoint of privacy and security プ ラ イ バ シ ー Privacy and security issues and impacts related to AI and IoT About various guidelines on AI and IoT Privacy and security measures to use AI and IoT effectively

Financial 25 years

General financial products (stocks, bonds, foreign exchange, off-balance products, etc.) Mainly introduce systems for financial institutions such as life insurance companies, securities, and banks. (10 years experience, requirement definition, design, development / unit test, integration / comprehensive test) Experience in frameworks such as Struts, Spring, TERASOLUNA, etc. Development experience in multiple languages ​​such as C #, Objective-C, waterfall type development ( Design, manufacturing, unit test, integration test) $ 15

Agile development (from requirement definition to release) {15 years} * Both styles can be supported. Explanation materials creation and presentation (training materials, technical reports, etc.)

PMO (PM manager) through issue management, issue analysis, etc.

ERP business 35 years

SAP, ORCALE, Dynamics, Salesforce system, SAPFI / CO / SD / MM / PP / BI / BO / BW / BASIS consultant Customization (analysis, design, implementation) experience, ABAP development, Java technology experience 35 years or more Notes experience 10 More than a year

Dynamics introduction consultant (analysis, design, introduction) more than 28 years experience, ORCALE introduction consultant (analysis, design, introduction) experience more than 15 years

35+ years of IT experience including more than 15 years of Salesforce consultant experience and development on Salesforce.com CRM platform and more than 15 years of Java technology experience

Strong knowledge in Salesforce administration and customization, DataValidation, sales, marketing, customer service and support development teams. Experience in creating role hierarchies, custom profiles and public.Groups and managing users. Analyze your organization's processes, translate business workflows into accurate Salesforce.com workflows, and business experiences in creating custom objects, custom fields, page layouts, custom tabs, reports and various other components Client and application requirements according to extensive experience in Salesforce.com configuration to meet .Hands. Extensive business knowledge and experience in customizing various salesforce.com standard objects like accounts, contacts, opportunities, product and price books, cases, leads, campaigns, forecasts, reports and dashboards. Knowledge of roles, profiles, email templates, page layouts, workflows, workflow actions and approvals Process.Coordinated and detailed process documentation on issues for future follow-up and knowledge of offshore team.Experience in creating the deployment process Transfer the creation experience. Team players with good leadership and interpersonal skills, the ability to work effectively as well as individually, as well as at all organizational levels. Involved in various stages of the software development life cycle (SDLC), including analysis, requirements gathering, architectural design, lead developers, extensions, testing, deployment, and maintaining a single object-oriented enterprise application. • Working experience with Force.com IDE, Data Loader, Apex Explorer and Salesforce.com sandbox environment. Custom objects, custom fields, role-based page layouts, custom tabs, custom reports, report folders, report extraction into various formats, Visualforce pages, snapshots, dashboards, Apex classes, controllers and triggers, various design designs Excellent work experience of client and other components like per application requirements.

AI case 18 years

AI finance

 Dai-ichi Life Insurance Co., Ltd. performs manual inspections and processes payment assessments in parallel with AI.

Japan Post Insurance will also start commissioning the Watson AI system.

US INSURFY applies artificial intelligence technology to simulate insurance agents.

Artificial intelligence technology introduced by Japanese insurance companies

In addition to artificial intelligence, MS & AD Insurance Group Holdings will also integrate with Iheiy Schen and save ¥ 16 billion annually by property and casualty insurance companies.

Sumitomo Mitsui's sales department will use artificial intelligence to handle the customer service and insurance application processes, and will transfer excess staff to support sales activities.

Despite the shrinking size of Japanese large banks, the goal of insurers is to use technology to increase employee productivity and improve customer service.

Other insurance companies, such as Tokio Marine Holdings, will introduce new technologies to reduce daily workload by 20-30% and damage Japan P & C Insurance Holdings.

AI is responsible for determining, scanning, and automatically processing insurance claims using hospital-provided injury records, patient medical histories, and more.

AI can read the language of the lips, innovate cooking, improve cancer diagnosis, recognize a variety of voice commands, is deep inside the organization, and exerts its strengths in the organization and operational processes.

Japanese Fukoku Life Insurance Company plans to introduce an artificial intelligence (AI) system in January to improve operational efficiency, but at a cost of about 30% of the staff in the payment valuation department. After all, it is a very expensive expense in Japan, artificial intelligence system is only 200 million yen, annual maintenance fee is about 15 million yen. You can save about 140 million yen.

The system can "read" the doctor's medical certificate and other documents to gather information needed for insurance coverage, such as medical records, length of stay, and surgery name. In addition, the system can check the customer's insurance policy and find special insurance terms to prevent negligence payments.

Processing large amounts of data is Watson's primary use at the Fukoku Life Insurance Company, and it turns out that the employees who took part in this work could be partially replaced by machines. Fukoku still has experts who make payment decisions,

Dai-ichi Life Insurance Co., Ltd. performs manual inspections and processes payment assessments in parallel with AI.

Japan Post Insurance will also start commissioning the Watson AI system.

FinTech (Finance Technology) Japan Insurance Company uses AI (Artificial Intelligence) to support insurance claims. The use of artificial intelligence by Fukoku Mutual Life Insurance is not a common phenomenon in the industry, but Japanese life insurance giant Fukoku Mutual Life InsurancThe artificial intelligence system introduced by e IBM Watson is based on the IBM Japan Watson system. According to IBM, the Watson AI system is a `` cognitive technology that can be thought of like a human '' and `` can analyze and understand all data, including unstructured text, images, audio, and video. '' . Medical certificates and other documents to gather information needed for insurance coverage, such as medical records, length of stay, and surgery name. In addition to determining claims, the Watson system can also examine a customer's insurance contract to find special insurance terms. This measure is believed to prevent negligence payments. The system will carry out a total of about 132,000 inspections per fiscal year. The final payment decision still needs to be made by dedicated people, but the AI ​​system will make reading medical records and other simple procedures more efficient. In terms of cost, the above artificial intelligence system costs about 200 million yen, and the annual maintenance cost is expected to be about 15 million yen. Nearly 30% of the layoffs will save a life insurance giant about $ 140 million a year.

Japan Post Insurance plans to introduce a Watson AI system, which will start trial operations in March 2017. Nippon Life Insurance started using it in December


Alibaba Ant Financial Insurance Data Artificial Intelligence Project Ant Financial Services Artificial Intelligence system is used for pricing, billing and indemnification of thousands of consumer insurance.

The Alibabaant Financial Insurance Data Technology Lab has released "Auto Insurance Points" that can accurately image and analyze the risks of car owners and quantify auto insurance standards ranging from 300 to 700. The higher the score, the lower the risk. For example, the risk of married or educated people tends to be lower than the risk of singles, and people traveling longer between two locations are more likely than those without a fixed travel route. Lower. In this manner, the overall precision pricing capability of the insurance industry has been improved by considering a number of different vehicle owners, including driving habits and other multidimensional factors. For individual customers, it is possible to get the insurance that best suits their situation and avoid unnecessary spending, and for businesses, by offering more competitive services and prices, From profits to losses. conversion

AI fraud prevention


US financial technology company ZestFinance, artificial intelligence fraud prevention project


Starting with traditional anti-fraud vulnerabilities, using deep learning of the machine, the machine gathers large amounts of heterogeneous and multi-source information to form a shared library. Later, using machine learning functions and model algorithm technology, we were able to quantify risk characteristic indicators from traditional historical data and establish an artificial intelligence fraud prevention model.

Lemonade, a US insurance company, uses an artificial intelligence program called "Maya" to calculate policyholder premium rates. "Maya" completes the main business of a series of traditional insurance agents, including responding to consumer consultations, interpreting insurance terms and sending insurance quotes.



Intelligent fixed losses are often applied to car insurance, automatically identifying models, license plates and damaged parts, minimizing human effort, obscure and replacement vehicles, and even P maps You can find the billing process. The risk of fraud is to achieve intellectual loss, save owner time, reduce staff workload, and improve service efficiency. The artificial intelligence technology used is image recognition technology + deep learning + NLP.

Image recognition can handle unstructured data such as handwriting conversion, document scanning / photography, and video and live photo classification. After image processing, the displayed text information can be processed faster using NLP.

Currently, artificial intelligence is mostly in the insurance industry, such as customer service, underwriting, nuclear compensation, fixed losses and other after-sales areas, and there are not many uses in the pre-sales area.

Artificial intelligence application during the billing process

AI can be applied to improve the billing process. The improved "non-contact" claims do not require manual intervention. The whole process will use artificial intelligence and other technologies to report claims, take photographic damage, review the system, and communicate with customers. This possibility is enormous, as the customer can file a claim throughout this process without having to pass the red tape.

Companies that automate billing processes have significantly reduced processing time and improved processing quality. AI claims can also help insurers better handle fraudulent claims. Each year, fraudulent claims cost the insurance industry more than $ 40 billion. In the past, to identify fraudulently, reports were manually groomed to identify incorrect charges, but AI algorithms identify data patterns from fraudulent patterns and possible fraudulent locations. Was.

Chat robot

Chatbots need natural language processing and sentiment analysis. Effective chatbots can handle customer input and verb requests and provide personalized services. In the insurance industry, chatbots can be used to answer basic questions, process claims, sell products, process transactions, or ensure that customers get the right insurance.

Sales and underwriting

AI can extract customer data and create complete customer documents that include customer preferences and corresponding insurance products.

The underwriting phase is often time consuming and expensive, such as annoying issues and premium investigations, and artificial intelligence can automate the entire process. Robots capture relevant data by scanning potential customers' social files to find trends and patterns. For example, people with a healthy lifestyle and a stable job may be classified as safe driving groups. In other words, insurance premiums can be reduced. AI can analyze data better than humans and predict each customer's risk more accurately, so they can provide insurance coverage to customers and avoid customers that are dangerous to the company.


Insurance relies on data that can affect a company's revenue and customer satisfaction. One of the biggest benefits is that you can better use your data to improve how your customers are audited. Information processing and wireless data transmission will be fast growing areas of the insurance industry. Many insurance companies offer discounts to customers who are willing to share driving data. In addition, by identifying GPS data patterns, estimating road and traffic conditions, and predicting and avoiding accidents, you can reduce the number of bills and attract more secure and satisfying customers.

Differentiated prices are gradually becoming a possible option

Artificial intelligence in the insurance industry "from the people" itself, using big data analytics, different pricing, or precision marketing for different policyholders.

2. AI fraud prevention feature overrides traditional manual identification

Artificial intelligence has also added a lot to the Chinese insurance industry's fraud prevention applications. Insurers estimate that the cost of insurance fraud in China currently accounts for 15% to 20% of the costs incurred by insurance companies.

3, AI with a shared economic model to establish a claim resource cloud platform

4, the virtual agent shouted to remove the complex body can not afford to end

Introducing AI virtual insurance agents to replace weak institutions can greatly improve the past.

Of course, the role of AI is not only a substitute, but also a new level of professional skills. Artificial intelligence can quickly become an insurance professional through data entry and training. It can also be a customized insurance product that is not possible with professional human agents.

AI + insurance mode

1. Insurance industry characteristics limit data collection speed: Using AI to improve decision making is the perfect solution for the insurance industry to solve future problems. Unlike the banking industry, the insurance industry uses a decentralized storage mechanism.

2. Under asymmetric information, it is difficult to guarantee user security.

After AI is applied, the product scene is better presented because it can calculate the most rational solution for different situations.

MIT MIT scientists are building a physiological basis. An artificial intelligence system that distinguishes human emotions from messages and voice conversations by collecting large amounts of physiological and audio data through wearable devices to improve the accuracy of recognizing human emotions.

3, abstract attention, but figurative indifference to technology:

Baker & Hostetler in the United States is responsible for assisting with issues related to corporate bankruptcy. Ross, a law firm AI robot, reads existing laws and literature, draws conclusions from it, answers questions in specific cases, and provides guidance to those who use natural language questions. I can. With machine learning, you can continuously improve your ability to answer questions from past lawsuits and human interactions.

Embedded control 28 years

Development of semiconductor PCBA circuit design technology software

Development communication of transport control software for semiconductor manufacturing equipment

Embedded (control) firmware development using assembler

Development of automotive related software

PLC device control software

Information appliance firmware development

Development of various OS drivers for information appliances

Responsible for designing control software for mounting surveillance cameras

mplemented in the sports field of `` I ・ TOP Yokohama '' launched in 2017 by the city of Yokohama to promote industrial utilization and new business creation utilizing IoT, big data and AI ”Will create concrete ideas for the use of sports data generated by students and citizens' sports experiences in Yokohama through seminars and dialogues with companies and organizations in Yokohama related to sports. With a better understanding of the players, patrons, visitors, fans and customers you will demonstrate, you can win on the field, on the screen and on the world stage. Leverage SAP software to streamline operations and “visualize” customer data and analytics to improve player and team performance, operate venues more simply, and maximize revenue. Development of smartphone applications and games Development of websites of major companies ・ Development of AI and VR systems AI baseball AI automatically identifies the faces of professional baseball players. Processing 3,000 photos per game in minutes-Microsoft's AI implemented in Fujifilm's IMAGE WORKS, advanced technology and sports also use AI to analyze battle situation, new AR competition, and how to use AI for VAR Let's consider if there is any.

VAR is a system in which an assistant referee who performs video surveillance in a separate room for important judgments in a game "helps" judgments. The basis is a system that uses technology to prevent misjudgment. The specific method is that when a delicate decision is made, the referee pauses the game once with a gesture representing a square monitor with both hands. If the referee and assistant referee need to communicate over the air, the referee will also check the video to determine if there was no false referee and the decision was valid. This sequence is called a "review."

This is an AI soccer simulation equipped with the world's first soccer game situation prediction AI (artificial intelligence). Challenge to reproduce the soccer game using AI developed independently. Predict game results such as J-League based on simulation. The AI ​​actually plays the card that the team and each player are planning to play 100 times, and the game predicts the match result, including the fighting rate and score. Winning or losing, of course, counter attack. For example, side attack, entry into the vital area, build-up with a variable system, etc., the situation where the score is easy to determine in each game is not only A but also toto prediction such as compatibility of match cards, weather, home & away, recent performance of each player Equipped with necessary dashboard function. AI predicts not only the win / loss prediction but also the turbulence index such as the probability of giant killing. We will continue to research and develop dashboards necessary for toto prediction using various football big data. Toshiba and Toshiba have developed a system to automatically classify key plays required for rugby tactics analysis while acquiring the positions of players and balls using image processing and deep learning for rugby match videos shot with one camera. Developed jointly. While detecting and tracking players and balls in the video using deep learning, it associates the camera's field of view with the ground and obtains the coordinates of the players and balls on the field. Then, based on their positional relationships and movements, automatic classification of play such as passes, scrums and kicks is performed. This allows the team's analysts to focus on more advanced tactical analysis after the match, using automatically categorized statistics. The judgment support system is considered to be a “robot referee” that makes judgments and scores based on objective observations and data analysis. However, at present, we are only in a position to support judgments. You. Technically, there are some competitions that can be automated, but the decision to leave the decision completely to the machine is something that neither the judge nor the viewer can accept. The same is true of tactical analysis.In the previous rugby case, the current situation is to provide statistical data to analysts quickly, and then detailed tactical analysis and specific strategic planning are performed by expert analysts. Work. If data of many games is accumulated, it will be technically possible to realize AI that even proposes new tactics. This may come when a team with smarter AI technology always wins. Personally, I think that a collaborative relationship, in which humans perform more creative intellectual activities using the various analytical data provided by AI, is ideal. The rugby match against Waseda is very close every year, and is very exciting. I go to watching games every year, but even if the times change and people change, I feel that the traditional play style of Keio and Waseda rugby continues to be inherited. There is no doubt that something that has nothing to do with AI is working, while using the data effectively as data while enhancing the players who ultimately play. In any case, technological innovations often occur through big events such as the Olympics and World Cup. What kind of new technologies will be used in the Tokyo Olympics? Evolving athlete, coach, and referee technology ICT × Sports base is data conversion / visualization of exercise state Regardless of the use of AI, the base of ICT use in the sports field is `` Data conversion of player movements and overall team play / Visualization ”. The widespread use of this data has made it possible to accumulate a large amount of various data. By analyzing these data from various aspects, activities such as improving the accuracy of play and strengthening tactics have been in full swing.

Supporting player skill improvement with ICT First of all, there is support for player skill improvement. If the movements of the players can be visualized by sensors and image processing, the movements can be accurately and intuitively grasped, so that correction points can be easily found.

A typical example is a form check for golf swing operations. You can objectively catch bad habits by taking a picture of the golf swing with a camera.However, by attaching a sensor or processing and displaying the captured image, the movement of the body can be more accurately determined. Analyze and help seniors and coaches point out points to fix.

見 え る Also, visualization is useful when you check your form again after repeating the practice of correcting the indicated part.

Attempts have also begun to acquire skills to win matches by digitizing and visualizing not only forms but also the entire game itself. For example, in the summer of 2017, the Japan Windsurfing Association conducted an IoT demonstration experiment with Fujitsu and Lapis Semiconductor to improve the sailing skills of windsurfers.

In this demonstration experiment, a device that can simultaneously record GPS information and sensor information developed by Lapis Semiconductor was installed on a windsurfing sail, and the collected data was analyzed using Fujitsu's cloud service, and the movement of the sale was displayed in 3D models and graphs. Visualization is realized.

で き る Because the sale operation can be grasped as data, athletes can check the difference between the sale operation of the top players and their own sale operation with 3D models and numerical values, and verify the improvement of their own sailing.

Opponent tactics analysis

In competitive professional sports, it is used as basic data to analyze tactics of opponents. In competitive sports such as tennis, volleyball, and soccer, as much as improving one's own skills, identifying the tactics of the opponent and assembling one's own tactics is an important factor in winning the opponent.

It is common practice in amateur sports to analyze match data of opponents before the match and prepare play and tactics that contain the characteristics of the players.

One of the most advanced attempts is to collect real-time play data during a match, analyze the game situation from the collected data, find more effective tactics, and convey them to the players in the match.

For example, the WTA (Women's Tennis Association), a women's professional tennis competition organization, has introduced a system called “on-court coaching” that allows coaches to enter the court and instruct players during a game or set during a game. .

The coach can explain to the players why they are outstretched by showing the data during the game using the terminal and instruct the players to correct their tactics.

 It is said that the game itself became more interesting as both opponents modified their tactics in a flexible manner, increasing the number of competitive games.

Player condition management

In the field of team-matched professional sports, activities to help manage the conditions of players are expanding. In team-matched professional sports, the performance of high-priced athletes greatly affects the team's performance, so protecting the players from injuries and shortening the period of retirement due to injuries is a paramount proposition.


For example, Leicester City FC, a British Premier League professional soccer team, has provided players with GPS device wear that incorporates various sensors, such as GPS and accelerometers, in order to accurately understand how players load during a game. Have to wear.

If you wear it and play a game, you can collect exercise data such as total mileage, distance traveled at top speed, acceleration and deceleration for each player, and compare these data with the situation of injury. Thus, the correlation between the load situation and the type of exercise and the injury can be found for each player in detail.

分析 This analysis shows that each player is likely to be injured, so it is possible to reduce the frequency of injuries by managing the physical condition of each player in detail and resting tired players.

In fact, Leicester City FC had the fewest injuries of any Premier League team in the 2015-2016 season, when it won the English Premier League.

AI replaces human judgments Automatic machine learning: Providing the strength to win in competitions

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