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A wave-shaped CNN for marine-raft aquaculture-area extraction in SAR images

文献类型：期刊论文

作者Guo, Yanjun4; Du, Yunyan3,4; Yan, Ming2; Xie, Ting1; Liu, Moyun2,3; Wang, Nan4
刊名COMPUTERS AND ELECTRONICS IN AGRICULTURE
出版日期2025-05-01
卷号232页码:110078
关键词Remote sensing Synthetic aperture radar (SAR) images Marine-floating-raft aquaculture Deep learning Convolutional neural network (CNN)
ISSN号0168-1699
DOI10.1016/j.compag.2025.110078
产权排序1
文献子类Article
英文摘要This paper introduces an innovative deep convolutional neural network, the wave-shaped CNN, tailored for the robust extraction of a marine-raft aquaculture area (MRAA) from synthetic-aperture-radar (SAR) images. Confronting the intricate challenges posed by coherent noise, environmental variability, and the distinction between rafting areas and their background within SAR images, the proposed wave-shaped CNN provides a novel solution for dynamic MRAA monitoring, which collaboratively incorporates the feature-attention subnetwork (FAS) and feature-refinement subnetwork (FRS) with residual connections to refine the feature- extraction process. Specifically, the FAS can adeptly extract both comprehensive global and nuanced local features from the multi-scale characteristics of SAR images. Furthermore, the FRS introduces a series of Nshaped subnetworks aimed at addressing the prevalent issue of edge adhesion observed within SAR images. In addition, a specialized SAR-MRAA dataset is developed, which allows for enriching the resource for the MRAA task in SAR images. Comprehensive experimental analyses conducted on the proposed wave-shaped CNN show its superior performance and effectiveness in MRAA extraction, demonstrating its advantages in establishing baselines within this domain. The code is available at https://github/gmy63000/Wave-shaped-CNN.
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WOS研究方向Agriculture ; Computer Science
语种英语
WOS记录号WOS:001428421200001
出版者ELSEVIER SCI LTD
源URL[http://ir.igsnrr.ac.cn/handle/311030/213229]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Du, Yunyan
作者单位1.Chongqing Univ Technol, Math Sci Res Ctr, 69 Hongguang Ave, Chongqing 400054, Peoples R China
2.ASTAR, Inst High Performance Comp IHPC, 1 Fusionopolis Way 16-16 Connexis North Tower SG, Singapore 138632, Singapore;
3.ASTAR, Ctr Frontier AI Res CFAR, 1 Fusionopolis Way 16-16 Connexis North Tower SG, Singapore 138632, Singapore;
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, 11A Datun Rd, Beijing 100101, Peoples R China;
推荐引用方式
GB/T 7714		 Guo, Yanjun,Du, Yunyan,Yan, Ming,et al. A wave-shaped CNN for marine-raft aquaculture-area extraction in SAR images[J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE,2025,232:110078.
APA Guo, Yanjun,Du, Yunyan,Yan, Ming,Xie, Ting,Liu, Moyun,&Wang, Nan.(2025).A wave-shaped CNN for marine-raft aquaculture-area extraction in SAR images.COMPUTERS AND ELECTRONICS IN AGRICULTURE,232,110078.
MLA Guo, Yanjun,et al."A wave-shaped CNN for marine-raft aquaculture-area extraction in SAR images".COMPUTERS AND ELECTRONICS IN AGRICULTURE 232(2025):110078.

入库方式： OAI收割

来源：地理科学与资源研究所

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