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Review of deep learning-based algorithms for ship target detection from remote sensing images
Z. Huang; F. Wu; Y. Fu; Y. Zhang and X. Jiang
2023
发表期刊Guangxue Jingmi Gongcheng/Optics and Precision Engineering
ISSN1004924X
卷号31期号:15页码:2295-2318
摘要The detection of naval targets is a key area of research interest in the field of remote sensing im⁃ age processing and pattern recognition. Moreover,the automatic detection of naval targets is crucial to both civil and military applications. In this study,we discuss and analyze the advantages and disadvantages of typical deep-learning-based target-detection algorithms,compare and summarize them,and summarize state-of-the-art deep-learning-based ship target detection methods. We also provide a detailed introduction to five aspects of state-of-the-art ship target detection methods,including multi-scale detection,multi-an⁃ gle detection,small target detection,model light-weighting,and large-format wide remote sensing imag⁃ ing. We also introduce the common evaluation criteria of ship target recognition algorithms and existing ship image datasets,and discuss the current problems faced by ship target detection algorithms using re⁃ mote sensing images and future development trends in the field. © 2023 Chinese Academy of Sciences. All rights reserved.
DOI10.37188/OPE.20233115.2295
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条目标识符http://ir.ciomp.ac.cn/handle/181722/67542
专题中国科学院长春光学精密机械与物理研究所
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Z. Huang,F. Wu,Y. Fu,et al. Review of deep learning-based algorithms for ship target detection from remote sensing images[J]. Guangxue Jingmi Gongcheng/Optics and Precision Engineering,2023,31(15):2295-2318.
APA Z. Huang,F. Wu,Y. Fu,&Y. Zhang and X. Jiang.(2023).Review of deep learning-based algorithms for ship target detection from remote sensing images.Guangxue Jingmi Gongcheng/Optics and Precision Engineering,31(15),2295-2318.
MLA Z. Huang,et al."Review of deep learning-based algorithms for ship target detection from remote sensing images".Guangxue Jingmi Gongcheng/Optics and Precision Engineering 31.15(2023):2295-2318.
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