{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T19:51:17Z","timestamp":1778788277187,"version":"3.51.4"},"reference-count":74,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,2,2]],"date-time":"2023-02-02T00:00:00Z","timestamp":1675296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62071084"],"award-info":[{"award-number":["62071084"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["145109218"],"award-info":[{"award-number":["145109218"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Leading Talents Project of the State Ethnic Affairs Commission","award":["62071084"],"award-info":[{"award-number":["62071084"]}]},{"name":"Leading Talents Project of the State Ethnic Affairs Commission","award":["145109218"],"award-info":[{"award-number":["145109218"]}]},{"name":"the Fundamental Research Funds in Heilongjiang Provincial Universities","award":["62071084"],"award-info":[{"award-number":["62071084"]}]},{"name":"the Fundamental Research Funds in Heilongjiang Provincial Universities","award":["145109218"],"award-info":[{"award-number":["145109218"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent years, convolutional neural networks (CNNs) have been introduced for pixel-wise hyperspectral image (HSI) classification tasks. However, some problems of the CNNs are still insufficiently addressed, such as the receptive field problem, small sample problem, and feature fusion problem. To tackle the above problems, we proposed a two-branch convolutional neural network with a polarized full attention mechanism for HSI classification. In the proposed network, two-branch CNNs are implemented to efficiently extract the spectral and spatial features, respectively. The kernel sizes of the convolutional layers are simplified to reduce the complexity of the network. This approach can make the network easier to be trained and fit the network to small sample size conditions. The one-shot connection technique is applied to improve the efficiency of feature extraction. An improved full attention block, named polarized full attention, is exploited to fuse the feature maps and provide global contextual information. Experimental results on several public HSI datasets confirm the effectiveness of the proposed network.<\/jats:p>","DOI":"10.3390\/rs15030848","type":"journal-article","created":{"date-parts":[[2023,2,3]],"date-time":"2023-02-03T03:36:57Z","timestamp":1675395417000},"page":"848","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Two-Branch Convolutional Neural Network with Polarized Full Attention for Hyperspectral Image Classification"],"prefix":"10.3390","volume":"15","author":[{"given":"Haimiao","family":"Ge","sequence":"first","affiliation":[{"name":"College of Computer and Control Engineering, Qiqihar University, Qiqihar 161000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liguo","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Information and Communication Engineering, Dalian Minzu University, Dalian 116600, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Moqi","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer and Control Engineering, Qiqihar University, Qiqihar 161000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuexia","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Computer and Control Engineering, Qiqihar University, Qiqihar 161000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Computer and Control Engineering, Qiqihar University, Qiqihar 161000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haizhu","family":"Pan","sequence":"additional","affiliation":[{"name":"College of Computer and Control Engineering, Qiqihar University, Qiqihar 161000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanzhong","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer and Control Engineering, Qiqihar University, Qiqihar 161000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3972","DOI":"10.1109\/JSTARS.2022.3174412","article-title":"Fine-Grained Classification of Urban Functional Zones and Landscape Pattern Analysis Using Hyperspectral Satellite Imagery: A Case Study of Wuhan","volume":"15","author":"Yuan","year":"2022","journal-title":"IEEE J. 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