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:	Yue YU, Chen WANG, Jun SHI, Chongben TAO, Liang LI, Xinxin TANG, Liming ZHOU, Shunjun WEI, Xiaoling ZHANG
格式:	Artigo
语言:	Inglês
出版:	China Science Publishing & Media Ltd. (CSPM) 2024-10-01
丛编:	Leida xuebao
主题:	synthetic aperture radar (sar) label noise label noise correction label noise uncertainty modeling fuzzy clustering algorithm
在线阅读:	https://radars.ac.cn/cn/article/doi/10.12000/JR24130
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