Modeling and Correction of Label Noise Uncertainty for SAR ATR
The success of deep supervised learning in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) relies on a large number of labeled samples. However, label noise often exists in large-scale datasets, which highly influence network training. This study proposes loss curve fitting-based l...
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| Principais autores: | , , , , , , , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
China Science Publishing & Media Ltd. (CSPM)
2024-10-01
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| Serier: | Leida xuebao |
| Fag: | |
| Online adgang: | https://radars.ac.cn/cn/article/doi/10.12000/JR24130 |
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