Contrastive Open-Set Active Learning-Based Sample Selection for Image Classification
In this paper, we address a complex but practical scenario in Active Learning (AL) known as open-set AL, where the unlabeled data consists of both in-distribution (ID) and out-of-distribution (OOD) samples. Standard AL methods will fail in this scenario as OOD samples are highly likely to be regarde...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 33(2024) vom: 04., Seite 5525-5537
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| 1. Verfasser: |
Yan, Zizheng
(VerfasserIn) |
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| Weitere Verfasser: |
Ruan, Delian,
Wu, Yushuang,
Huang, Junshi,
Chai, Zhenhua,
Han, Xiaoguang,
Cui, Shuguang,
Li, Guanbin |
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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 image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article |
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