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of Agriculture and Agri-Product Safety of the Ministry of Education of China","award":["yzuxk202008"],"award-info":[{"award-number":["yzuxk202008"]}]},{"name":"Open Project for Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education of China","award":["CX(22)3149"],"award-info":[{"award-number":["CX(22)3149"]}]},{"name":"Open Project for Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education of China","award":["JILAR-KF202102"],"award-info":[{"award-number":["JILAR-KF202102"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In order to categorize feature classes by capturing subtle differences, hyperspectral images (HSIs) have been extensively used due to the rich spectral-spatial information. The 3D convolution-based neural networks (3DCNNs) have been widely used in HSI classification because of their powerful feature extraction capability. However, the 3DCNN-based HSI classification approach could only extract local features, and the feature maps it produces include a lot of spatial information redundancy, which lowers the classification accuracy. To solve the above problems, we proposed a spatial attention network (SATNet) by combining 3D OctConv and ViT. Firstly, 3D OctConv divided the feature maps into high-frequency maps and low-frequency maps to reduce spatial information redundancy. Secondly, the ViT model was used to obtain global features and effectively combine local-global features for classification. To verify the effectiveness of the method in the paper, a comparison with various mainstream methods on three publicly available datasets was performed, and the results showed the superiority of the proposed method in terms of classification evaluation performance.<\/jats:p>","DOI":"10.3390\/rs14225902","type":"journal-article","created":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T03:13:41Z","timestamp":1669086821000},"page":"5902","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["SATNet: A Spatial Attention Based Network for Hyperspectral Image Classification"],"prefix":"10.3390","volume":"14","author":[{"given":"Qingqing","family":"Hong","sequence":"first","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education of China, Jiangsu Province Engineering Research Center of Knowledge Management and Intelligent Service, College of Information Engineer, Yangzhou University, Yangzhou 225009, China"}]},{"given":"Xinyi","family":"Zhong","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education of China, Jiangsu Province Engineering Research Center of Knowledge Management and Intelligent Service, College of Information Engineer, Yangzhou University, Yangzhou 225009, China"}]},{"given":"Weitong","family":"Chen","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Joint International Research Laboratory of Agriculture and 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Agriculture and Agri-Product Safety of the Ministry of Education of China, Jiangsu Province Engineering Research Center of Knowledge Management and Intelligent Service, College of Information Engineer, Yangzhou University, Yangzhou 225009, China"}]},{"given":"Hao","family":"Sun","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education of China, Jiangsu Province Engineering Research Center of Knowledge Management and Intelligent Service, College of Information Engineer, Yangzhou University, Yangzhou 225009, China"}]},{"given":"Tianbao","family":"Yang","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Joint International Research 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