Invention Grant
- Patent Title: Proposal learning for semi-supervised object detection
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Application No.: US17080276Application Date: 2020-10-26
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Publication No.: US11669745B2Publication Date: 2023-06-06
- Inventor: Chetan Ramaiah , Peng Tang , Caiming Xiong
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: salesforce.com, inc.
- Current Assignee: salesforce.com, inc.
- Current Assignee Address: US CA San Francisco
- Agency: Haynes and Boone, LLP
- Main IPC: G06F18/21
- IPC: G06F18/21 ; G06N3/082 ; G06F18/214

Abstract:
A method for generating a neural network for detecting one or more objects in images includes generating one or more self-supervised proposal learning losses based on the one or more proposal features and corresponding proposal feature predictions. One or more consistency-based proposal learning losses are generated based on noisy proposal feature predictions and the corresponding proposal predictions without noise. A combined loss is generated using the one or more self-supervised proposal learning losses and one or more consistency-based proposal learning losses. The neural network is updated based on the combined loss.
Public/Granted literature
- US20210216828A1 PROPOSAL LEARNING FOR SEMI-SUPERVISED OBJECT DETECTION Public/Granted day:2021-07-15
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