- Patent Title: Deep learning architecture for automated image feature extraction
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Application No.: US15854971Application Date: 2017-12-27
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Publication No.: US10796221B2Publication Date: 2020-10-06
- Inventor: Min Zhang , Gopal Biligeri Avinash
- Applicant: General Electric Company
- Applicant Address: US NY Schenectady
- Assignee: General Electric Company
- Current Assignee: General Electric Company
- Current Assignee Address: US NY Schenectady
- Agency: Amin, Turocy & Watson, LLP
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06N3/04 ; G06N3/08 ; G16H30/40 ; G06N20/20 ; G06K9/62 ; G06T7/00

Abstract:
Systems and techniques for facilitating a deep learning architecture for automated image feature extraction are presented. In one example, a system includes a machine learning component. The machine learning component generates learned imaging output regarding imaging data based on a convolutional neural network that receives the imaging data. The machine learning component also performs a plurality of sequential and/or parallel downsampling and upsampling of the imaging data associated with convolutional layers of the convolutional neural network.
Public/Granted literature
- US20190122074A1 DEEP LEARNING ARCHITECTURE FOR AUTOMATED IMAGE FEATURE EXTRACTION Public/Granted day:2019-04-25
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