MLBR-YOLOX: An Efficient SAR Ship Detection Network With Multilevel Background Removing Modules

On the remote sensing images of marine synthetic aperture radar (SAR), ship targets often occupy only a small part of an image, and the rest are all sea and coastal backgrounds. Existing neural networks based on SAR ship detection often directly detect an entire SAR image, which consumes a large amo...

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Bibliographic Details

Published in:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Main Authors:	Jindong Zhang, Weixing Sheng, Hairui Zhu, Shanhong Guo, Yubing Han
Format:	Article
Language:	English
Published:	IEEE 2023-01-01
Subjects:	Convolutional neural network (CNN) multilevel background removing modules ship detection synthetic aperture radar (SAR) image
Online Access:	https://ieeexplore.ieee.org/document/10137739/