Invention Grant
- Patent Title: Methods and apparatus for discriminative semantic transfer and physics-inspired optimization of features in deep learning
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Application No.: US18142997Application Date: 2023-05-03
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Publication No.: US12079713B2Publication Date: 2024-09-03
- Inventor: Anbang Yao , Hao Zhao , Ming Lu , Yiwen Guo , Yurong Chen
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Compass IP Law PC
- Main IPC: G06V10/82
- IPC: G06V10/82 ; G06F18/214 ; G06N3/04 ; G06N3/063 ; G06N3/08 ; G06V10/44 ; G06V10/764 ; G06V10/94 ; G06V20/10 ; G06V20/40 ; G06V20/70

Abstract:
Methods and apparatus for discrimitive semantic transfer and physics-inspired optimization in deep learning are disclosed. A computation training method for a convolutional neural network (CNN) includes receiving a sequence of training images in the CNN of a first stage to describe objects of a cluttered scene as a semantic segmentation mask. The semantic segmentation mask is received in a semantic segmentation network of a second stage to produce semantic features. Using weights from the first stage as feature extractors and weights from the second stage as classifiers, edges of the cluttered scene are identified using the semantic features.
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