Low-Dimensional Gradient Helps Out-of-Distribution Detection
Detecting out-of-distribution (OOD) samples is essential for ensuring the reliability of deep neural networks (DNNs) in real-world scenarios. While previous research has predominantly investigated the disparity between in-distribution (ID) and OOD data through forward information analysis, the discr...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 12 vom: 12. Dez., Seite 11378-11391
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| 1. Verfasser: |
Wu, Yingwen
(VerfasserIn) |
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| Weitere Verfasser: |
Li, Tao,
Cheng, Xinwen,
Yang, Jie,
Huang, Xiaolin |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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