Invention Application
- Patent Title: SELF-SUPERVISED LEARNING FRAMEWORK TO GENERATE CONTEXT SPECIFIC PRETRAINED MODELS
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Application No.: US17889201Application Date: 2022-08-16
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Publication No.: US20230052078A1Publication Date: 2023-02-16
- Inventor: Pavan Annangi , Deepa Anand , Bhushan Patil , Rahul Venkataramani
- Applicant: GE Precision Healthcare LLC
- Applicant Address: US WI Wauwatosa
- Assignee: GE Precision Healthcare LLC
- Current Assignee: GE Precision Healthcare LLC
- Current Assignee Address: US WI Wauwatosa
- Priority: IN202141037094 20210816
- Main IPC: G06V10/778
- IPC: G06V10/778 ; G06V10/20 ; G06V10/26 ; G16H30/40

Abstract:
Systems and methods for self-supervised representation learning as a means to generate context-specific pretrained models include selecting data from a set of available data sets; selecting a pretext task from domain specific pretext tasks; selecting a target problem specific network architecture based on a user selection from available choices or any customized model as per user preference; and generating a pretrained model for the selected network architecture using the selected data obtained from the set of available data sets and a pretext task as obtained from domain specific pretext tasks.
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