The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 03, 2021

Filed:

May. 25, 2017
Applicant:

Metail Limited, London, GB;

Inventors:

Yu Chen, London, GB;

Sukrit Shankar, London, GB;

Jim Downing, London, GB;

Joe Townsend, London, GB;

Duncan Robertson, London, GB;

Tom Adeyoola, London, GB;

Assignee:

METAIL LIMITED, London, GB;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 15/00 (2011.01); G06F 16/583 (2019.01); G06F 16/538 (2019.01); G06F 16/535 (2019.01); G06F 40/20 (2020.01); G06K 9/62 (2006.01); G06N 3/08 (2006.01); G06T 15/04 (2011.01);
U.S. Cl.
CPC ...
G06T 15/005 (2013.01); G06F 16/535 (2019.01); G06F 16/538 (2019.01); G06F 16/5838 (2019.01); G06F 16/5862 (2019.01); G06F 40/20 (2020.01); G06K 9/6256 (2013.01); G06K 9/6267 (2013.01); G06N 3/08 (2013.01); G06T 15/04 (2013.01);
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.


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