Method and system for predicting garment attributes using deep learning
US11080918B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 25, 2017 |
| Grant date | Aug 3, 2021 |
| Priority date | — |
| Expiry date | Oct 21, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/12
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
There is provided a computer implemented method for predicting garment or accessory attributes using deep learning techniques, comprising the steps of: (i) receiving and storing one or more digital image datasets including images of garments or accessories; (ii) training a deep model for garment or accessory attribute identification, using the stored one or more digital image datasets, by configuring a deep neural network model to predict (a) multiple-class discrete attributes; (b) binary discrete attributes, and (c) continuous attributes, (iii) receiving one or more digital images of a garment or an accessory, and (iv) extracting attributes of the garment or the accessory from the one or more received digital images using the trained deep model for garment or accessory attribute identification. A related system is also provided.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.