Ikkyo Technology - Categorific
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Ikkyo Technology is a Kobe/Japan based startup focusing on Deep Learning and Machine Learning. Categorific is WebAPI that automatically connects and sorts out visual contents in the database based on their visual similarity.
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Ikkyo Technology - Categorific
- 2. PROBLEM • Web services are overwhelmed by the rapidly growing amount of user-generated visual contents • There is no easy way for them to organise those visual data in their database other than worker-intensive text-tagging solution
- 3. SOLUTION • WebAPI that automatically connects and sorts out visual contents in the database based on their visual similarity • Cost efficient engine that charges the users based on the actual usage or the performance
- 4. CATEGORIFIC CASE I! ! To increase in-app stamp purchase for photo sharing app Categorific+Case+I
- 5. • Too many screen transitions to find good fitting stamps for each pictures • With Categorific, an app can recommend the most popular stamps based on the historical data that have the similar contents to a newly taken picture Categorific+Case+I
- 15. CATEGORIFIC CASE II! ! To add “search by image” option for e-commerce service Categorific+Case+II
- 16. • Only text search is available to look for an item from the long list of web-shops and items • With Categorific, “search by image” and “look for similar-looking items” functions can be easily added Categorific+Case+II
- 17. • With “search by image,” users can find many similar-taste items with ease • Users do not have to think about which text- wording would best describe a blue shirt Categorific+Case+II
- 18. CATEGORIFIC CASE III! ! To sort out visual items based on content similarity for better user- experience Categorific+Case+III
- 19. • Stamps are simply listed, and it is too difficult for users to find what they are looking for • With Categorific, an app can sort out stamps based on contents similarity for better user-experience Categorific+Case+III
- 21. 0 3,000,000 6,000,000 9,000,000 12,000,000 NOV DEC JAN FEB MAR APR # of cumulative procesed images 12 million Weprocessed! ! ! imagessofarfrom! 7companiesin! last6months TRACK RECORD
- 23. ADRIEN! Hacker / Engineer! ! ! YUKI! Co-Founder / CTO! ! ! ! ! YOSHI! Co-Founder / CEO! ! ! ! ICKO! Finance / Admin! ! ! ! MARTIN! Full Stack Engineer! ! ! Team+Introduction
- 24. ADRIEN! Hacker / Engineer! ! ! ! YUKI! Co-Founder / CTO! ! ! ! YOSHI! Co-Founder / CEO! ! ! ! MARTIN! Full Stack Engineer! ! ! ! MATTHEW! Engineer! ! ! NAKASHIMA! Engineer! ! ! TANAKA! Engineer! ! ! YOKO! Engineer! ! ! NORIMATSU! Researcher! Machine-Learning! ! HIO! Researcher! Data-Mining! ! +! ENGINEER RESEARCHER ICKO! Finance / Admin! ! ! ! WITH OUR SUPPORTING MEMBERS Team+ Introduction
- 25. APPENDIX I! ! Our real time motion capture technology for webcam recorded live video! ! “Online Conference System 2006-148425 (P2006-148425A)“ Appendix+I
- 27. APPENDIX II! ! Developing Computer-Vision supported heavy-machinery video camera in order to enhance safety at construction sites as a joint project with Kyoritsu Denshi Kogyo, the biggest crane-camera market share holder Appendix+II
- 29. APPENDIX III! ! AI (both Computer-Vision and Machine- Learning) supported visual contents moderation engine with our patent-pending “SmartAllocation" algorithm maximising human-computation efficiency to cut the existing moderation cost by 90% at the most Appendix+III
- 30. Filteringawayinappropriatevisualcontents • We reduced 90% of the existing human-only moderation cost for one of the world's biggest game companies without giving up moderation accuracy • We did not directly apply computer-vision based moderation results, but used them to only maximise human computation efficiency instead. Appendix+III
- 31. First Step! ! Developing suitable! classifiers for the! targeted contents by! our CV technology,! then applying them to! obtain ballpark results Second Step! ! Efficiently managing! task allocation by! continuously learning! from CV classifiers! and human output “SmartAllocation“! Ourpatent-pendingtechnology! Third Step! ! Human computation! part can be conducted! by crowdsourcing,! BPO companies, or! in-house community! management team Appendix+III
- 32. http://ikkyotech.com info@ikkyotech.com contact us for more info!!