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Semantic Space Analysis for Zero-Shot Learning on SAR Images

文献类型：期刊论文

作者Liu, Bo1; Xu, Jiping2; Zeng, Hui3,4; Dong, Qiulei1; Hu, Zhanyi1
刊名REMOTE SENSING
出版日期2024-07-01
卷号16期号:14页码:13
关键词semantic space analysis zero-shot learning SAR target classification
DOI10.3390/rs16142627
通讯作者Zeng, Hui(hzeng@ustb.edu.cn)
英文摘要Semantic feature space plays a bridging role from 'seen classes' to 'unseen classes' in zero-shot learning (ZSL). However, due to the nature of SAR distance-based imaging, which is drastically different from that of optical imaging, how to construct an appropriate semantic space for SAR ZSL is still a tricky and less well-addressed issue. In this work, three different semantic feature spaces, constructed using natural language, remote sensing optical images, and web optical images, respectively, are explored. Furthermore, three factors, i.e., model capacity, dataset scale, and pre-training, are investigated in semantic feature learning. In addition, three datasets are introduced for the evaluation of SAR ZSL. Experimental results show that the semantic space constructed using remote sensing images is better than the other two and that the quality of semantic space can be affected significantly by factors such as model capacity, dataset scale, and pre-training schemes.
资助项目National Natural Science Foundation of China[61991423] ; National Natural Science Foundation of China[62273034] ; Scientific and Technological Innovation Foundation of Foshan[BK21BF004] ; Open Project Program of Key Laboratory of Industrial Internet and Big Data, China National Light Industry, Beijing Technology and Business University
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001277370200001
出版者MDPI
资助机构National Natural Science Foundation of China ; Scientific and Technological Innovation Foundation of Foshan ; Open Project Program of Key Laboratory of Industrial Internet and Big Data, China National Light Industry, Beijing Technology and Business University
源URL[http://ir.ia.ac.cn/handle/173211/59379]  
专题自动化研究所_模式识别国家重点实验室_机器人视觉团队
通讯作者Zeng, Hui
作者单位1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.China Natl Light Ind, Key Lab Ind Internet & Big Data, Beijing 100048, Peoples R China
3.Univ Sci & Technol Beijing, Beijing Engn Res Ctr Ind Spectrum Imaging, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
4.Univ Sci & Technol Beijing, Shunde Innovat Sch, Foshan 528399, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Bo,Xu, Jiping,Zeng, Hui,et al. Semantic Space Analysis for Zero-Shot Learning on SAR Images[J]. REMOTE SENSING,2024,16(14):13.
APA Liu, Bo,Xu, Jiping,Zeng, Hui,Dong, Qiulei,&Hu, Zhanyi.(2024).Semantic Space Analysis for Zero-Shot Learning on SAR Images.REMOTE SENSING,16(14),13.
MLA Liu, Bo,et al."Semantic Space Analysis for Zero-Shot Learning on SAR Images".REMOTE SENSING 16.14(2024):13.

入库方式： OAI收割

来源：自动化研究所

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