Invention Grant
- Patent Title: Decoupling category-wise independence and relevance with self-attention for multi-label image classification
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Application No.: US16509391Application Date: 2019-07-11
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Publication No.: US11494616B2Publication Date: 2022-11-08
- Inventor: Sheng Guo , Weilin Huang , Matthew Robert Scott , Luchen Liu
- Applicant: Shenzhen Malong Technologies Co., Ltd.
- Applicant Address: CN Shenzhen
- Assignee: Shenzhen Malong Technologies Co., Ltd.
- Current Assignee: Shenzhen Malong Technologies Co., Ltd.
- Current Assignee Address: CN Shenzhen
- Agency: Shook, Hardy & Bacon L.L.P.
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06F17/15 ; G06K9/62 ; G06F17/18 ; G06V20/20

Abstract:
Methods and systems are provided for generating a multi-label classification system. The multi-label classification system can use a multi-label classification neural network system to identify one or more labels for an image. The multi-label classification system can explicitly take into account the relationship between classes in identifying labels. A relevance sub-network of the multi-label classification neural network system can capture relevance information between the classes. Such a relevance sub-network can decouple independence between classes to focus learning on relevance between the classes.
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