Invention Grant
- Patent Title: Convolutional neural network joint training
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Application No.: US15177121Application Date: 2016-06-08
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Publication No.: US10467529B2Publication Date: 2019-11-05
- Inventor: Zhe Lin , Yufei Wang , Radomir Mech , Xiaohui Shen , Gavin Stuart Peter Miller
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: SBMC
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

Abstract:
In embodiments of convolutional neural network joint training, a computing system memory maintains different data batches of multiple digital image items, where the digital image items of the different data batches have some common features. A convolutional neural network (CNN) receives input of the digital image items of the different data batches, and classifier layers of the CNN are trained to recognize the common features in the digital image items of the different data batches. The recognized common features are input to fully-connected layers of the CNN that distinguish between the recognized common features of the digital image items of the different data batches. A scoring difference is determined between item pairs of the digital image items in a particular one of the different data batches. A piecewise ranking loss algorithm maintains the scoring difference between the item pairs, and the scoring difference is used to train CNN regression functions.
Public/Granted literature
- US20170357892A1 Convolutional Neural Network Joint Training Public/Granted day:2017-12-14
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