Squeeze and Excitation Rank Faster R-CNN for Ship Detection in SAR Images

Synthetic aperture radar (SAR) ship detection is an important part of marine monitoring. With the development in computer vision, deep learning has been used for ship detection in SAR images such as the faster region-based convolutional neural network (R-CNN), single-shot multibox detector, and dens...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters Jg. 16; H. 5; S. 751 - 755
Hauptverfasser:	Lin, Zhao, Ji, Kefeng, Leng, Xiangguang, Kuang, Gangyao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.05.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Computer vision Data mining Deep learning Detection Excitation faster region-based convolutional neural network (R-CNN) Feature extraction Feature maps Image detection Image processing Image segmentation Machine learning Marine vehicles Methods Neural networks Performance enhancement Proposals Radar Radar detection Radar imaging SAR (radar) ship detection Ships Synthetic aperture radar synthetic aperture radar (SAR) Training
ISSN:	1545-598X, 1558-0571
Online-Zugang:	Volltext
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