Accurate and Robust Object Detection via Selective Adversarial Learning With Constraints
ConvNet-based object detection networks have achieved outstanding performance on clean images. However, many works have shown that these detectors perform poorly on corrupted images caused by noises, blurs, poor weather conditions and so on. With the development of security-sensitive applications, t...
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 5593-5605
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| 1. Verfasser: |
Chen, Jianpin
(VerfasserIn) |
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| Weitere Verfasser: |
Li, Heng,
Gao, Qi,
Liang, Junling,
Zhang, Ruipeng,
Yin, Liping,
Chai, Xinyu |
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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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