IA-CIOU: An Improved IOU Bounding Box Loss Function for SAR Ship Target Detection Methods

Ship detection in synthetic aperture radar (SAR) images is crucial in both civilian and military fields, offering extensive application prospects. Nonetheless, owing to the distinctive characteristics of SAR imaging, this task confronts numerous challenges. Specifically, ships with high aspect ratio...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing Jg. 17; S. 10569 - 10582
Hauptverfasser:	Huang, Pingping, Tian, Shihao, Su, Yun, Tan, Weixian, Dong, Yifan, Xu, Wei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Aspect ratio Classification algorithms Datasets Deep learning Feature extraction Intersection over union (IOU) loss function Marine vehicles Military applications Radar detection Radar imaging Radar polarimetry SAR (radar) ship detection Synthetic aperture radar synthetic aperture radar (SAR) images Target detection Task analysis YOLO YOLOv5
ISSN:	1939-1404, 2151-1535
Online-Zugang:	Volltext
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