A Novel Anchor-Free Model With Salient Feature Fusion Mechanism for Ship Detection in SAR Images

doi:10.1109/JSTARS.2023.3319831

CORC > 长春光学精密机械与物理研究所 > 中国科学院长春光学精密机械与物理研究所

	A Novel Anchor-Free Model With Salient Feature Fusion Mechanism for Ship Detection in SAR Images
	Y. Gao; C. Wu and M. Ren
刊名	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
	2023
卷号	16 页码:9089-9105
ISSN号	19391404
DOI	10.1109/JSTARS.2023.3319831
英文摘要	Ship detection in synthetic aperture radar (SAR) images has gained great attention in civil and military fields. Anchor-based detection algorithms usually rely on preset candidate boxes, and a large amount of anchor boxes with different sizes will result in a large amount of computing resources being consumed. Recently, anchor-free algorithms have found wide applications in ship detection from SAR images. However, there are still some problems which limit the ship detection performance to a certain extent, such as how to effectively fuse salient features and unbalanced distribution of positive samples. In order to tackle the above problems, we propose a novel anchor-free model named salient feature fusion (SFF)-YOLOX with SFF mechanism. First, we redesign the network of YOLOX to obtain the best balance between detection accuracy and running speed. Second, a saliency region extraction module is introduced to generate the corresponding salient guide map of the input image. Besides, the SFF mechanism is proposed by fusing deep features and salient features to better enhance the discrimination of the multiscale targets. Finally, we improve the SimOTA mechanism by combining the predicted intersection over union (IoUs) and the anchor IoUs to the ground truth bounding boxes to instruct label assignment. We evaluate the detection accuracy and running speed of SFF-YOLOX on the public dataset single shot detector and test the generalization ability on HRSID and two complex large-scale SAR images, and the experimental results prove the model's effectiveness for ship detection task in SAR images. © 2008-2012 IEEE.
URL标识	查看原文
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/67479]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	Y. Gao,C. Wu and M. Ren. A Novel Anchor-Free Model With Salient Feature Fusion Mechanism for Ship Detection in SAR Images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2023,16:9089-9105.
APA	Y. Gao,&C. Wu and M. Ren.(2023).A Novel Anchor-Free Model With Salient Feature Fusion Mechanism for Ship Detection in SAR Images.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,16,9089-9105.
MLA	Y. Gao,et al."A Novel Anchor-Free Model With Salient Feature Fusion Mechanism for Ship Detection in SAR Images".IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 16(2023):9089-9105.