数学与计算机科学 |
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基于半监督子空间迁移的稀疏表示遥感图像场景分类方法 |
周国华1,2,3, 蒋晖1,2, 顾晓清2, 殷新春3 |
1.常州工业职业技术学院 信息工程学院,江苏 常州 213164 2.常州大学 计算机与人工智能学院,江苏 常州 213164 3.扬州大学 信息工程学院,江苏 扬州 225127 |
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A sparse representation method based on semi-supervised transfer learning subspace for remote sensing scene classification |
ZHOU Guohua1,2,3, JIANG Hui1,2, GU Xiaoqing2, YIN Xinchun3 |
1.College of Information Engineering, Changzhou Institute of Industry Technology, Changzhou 213164,Jiangsu Province, China 2.School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, Jiangsu Province, China 3.College of Information Engineering, Yangzhou University, Yangzhou 225127, Jiangsu Province,China |
引用本文:
周国华, 蒋晖, 顾晓清, 殷新春. 基于半监督子空间迁移的稀疏表示遥感图像场景分类方法[J]. 浙江大学学报(理学版), 2021, 48(6): 684-693.
ZHOU Guohua, JIANG Hui, GU Xiaoqing, YIN Xinchun. A sparse representation method based on semi-supervised transfer learning subspace for remote sensing scene classification. Journal of Zhejiang University (Science Edition), 2021, 48(6): 684-693.
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https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2021.06.006
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https://www.zjujournals.com/sci/CN/Y2021/V48/I6/684
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