Brain-Inspired Fast Saliency-Based Filtering Algorithm for Ship Detection in High-Resolution SAR Images

In this article, we aim to improve the performance of synthetic aperture radar (SAR) ship detection under complex conditions. The complex backgrounds are commonly encountered for high-resolution (HR) SAR ship detection data set, and they greatly influence the detection performance of ships. In recen...

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Vydáno v:	IEEE transactions on geoscience and remote sensing Ročník 60; s. 1 - 9
Hlavní autoři:	Zhang, Panpan, Luo, Haibo, Ju, Moran, He, Miao, Chang, Zheng, Hui, Bin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Artificial neural networks Brain Brain-inspired deep neural networks (DNNs) Detection Detectors Fast Saliency-based Filtering algorithm (FSF) Feature extraction filtering mechanisms Filtration Focusing High resolution Image resolution Information processing Marine vehicles Neural networks Noise sensitivity Performance enhancement priority map Radar detection Radar polarimetry Resolution Salience saliency map SAR (radar) Synthetic aperture radar Visualization
ISSN:	0196-2892, 1558-0644
On-line přístup:	Získat plný text
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