inFashion Convolutional Neural Networks Applied to Computer Vision for Industrial Consumer Trend A
| Reference number | |
| Coordinator | Stockholms universitet - Institutionen för data- och systemvetenskap |
| Funding from Vinnova | SEK 1 965 500 |
| Project duration | July 2017 - June 2019 |
| Status | Completed |
Important results from the project
Incl. both researchers and industry partners proved to be useful. We suffered initially from low research staffing, due to a general lack of competence in the area. Both SU and RISE have made serious efforts. SU recruited a Ph.D. student that will continue working on the topic for another 3 years. RISE recruited new staff that was engaged in the project from 2018. Parallel tech development was useful, but we failed to integrate both parts, due to the required efforts in individual paths.
Expected long term effects
The results will have long term effects on the industry: 1)The technical results show that computer vision can be applied to fashion and provide machine trend analysis 2)The new staffing both at SU and RISE will have continuous effects and produce results long term 3)The foundation of the company Tenue Tech and Sarvai is set-up to exploit long term results of the fashion AI research
Approach and implementation
Incl. both researchers and industry partners proved to be useful. We suffered initially from low research staffing, due to a general lack of competence in the area. Both SU and RISE have made serious efforts. SU recruited a Ph.D. student that will continue working on the topic for another 3 years. RISE recruited new staff that was engaged in the project from 2018. Parallel tech development was useful, but we failed to integrate both parts, due to the required efforts in individual paths.