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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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 12 vom: 12. Dez., Seite 11378-11391
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| Auteur principal: |
Wu, Yingwen
(Auteur) |
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| Autres auteurs: |
Li, Tao,
Cheng, Xinwen,
Yang, Jie,
Huang, Xiaolin |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2024
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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