- Patent Title: System and method for optimization of deep learning architecture
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Application No.: US16334091Application Date: 2017-06-21
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Publication No.: US11017269B2Publication Date: 2021-05-25
- Inventor: Sheshadri Thiruvenkadam , Sohan Rashmi Ranjan , Vivek Prabhakar Vaidya , Hariharan Ravishankar , Rahul Venkataramani , Prasad Sudhakar
- Applicant: General Electric Company
- Applicant Address: US NY Niskayuna
- Assignee: General Electric Company
- Current Assignee: General Electric Company
- Current Assignee Address: US NY Niskayuna
- Priority: IN201641033618 20160930
- International Application: PCT/US2017/038504 WO 20170621
- International Announcement: WO2018/063460 WO 20180405
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G16H30/40 ; G06K9/46 ; G06N3/08 ; G06N3/04 ; G16H50/20 ; G16H40/63 ; G16H50/70

Abstract:
A method for determining optimized deep learning architecture includes receiving a plurality of training images and a plurality of real time images corresponding to a subject. The method further includes receiving, by a medical practitioner, a plurality of learning parameters comprising a plurality of filter classes and a plurality of architecture parameters. The method also includes determining a deep learning model based on the plurality of learning parameters and the plurality of training images, wherein the deep learning model comprises a plurality of reusable filters. The method further includes determining a health condition of the subject based on the plurality of real time images and the deep learning model. The method also includes providing the health condition of the subject to the medical practitioner.
Public/Granted literature
- US20190266448A1 SYSTEM AND METHOD FOR OPTIMIZATION OF DEEP LEARNING ARCHITECTURE Public/Granted day:2019-08-29
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