Invention Application
- Patent Title: SELF-CONTRASTIVE LEARNING FOR IMAGE PROCESSING
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Application No.: US17513493Application Date: 2021-10-28
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Publication No.: US20230138380A1Publication Date: 2023-05-04
- Inventor: Zhang Chen , Xiao Chen , Yikang Liu , Terrence Chen , Shanhui Sun
- Applicant: Shanghai United Imaging Intelligence Co., Ltd.
- Applicant Address: CN Shanghai
- Assignee: Shanghai United Imaging Intelligence Co., Ltd.
- Current Assignee: Shanghai United Imaging Intelligence Co., Ltd.
- Current Assignee Address: CN Shanghai
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T7/00 ; G06T5/00 ; G06T3/40 ; G06K9/00 ; G06T11/00 ; G06N3/08 ; G16H30/20 ; G01R33/56

Abstract:
A neural network system implements a model for generating an output image based on a received input image. The model is learned through a training process during which parameters associated with the model are adjusted so as to maximize a difference between a first image predicted using first parameter values of the model and a second image predicted using second parameter values of the model, and to minimize a difference between the second image and a ground truth image. During a first iteration of the training process the first image is predicted and during a second iteration the second image is predicted. The first parameter values are obtained during the first iteration by minimizing a difference between the first image and the ground truth image, and the second parameter values are obtained during the second iteration by maximizing the difference between the first image and the second image.
Public/Granted literature
- US11966454B2 Self-contrastive learning for image processing Public/Granted day:2024-04-23
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