{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T15:35:48Z","timestamp":1780500948866,"version":"3.54.1"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41672323"],"award-info":[{"award-number":["41672323"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/jstars.2021.3065706","type":"journal-article","created":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T20:46:52Z","timestamp":1615582012000},"page":"3415-3425","source":"Crossref","is-referenced-by-count":29,"title":["Center Attention Network for Hyperspectral Image Classification"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1482-5276","authenticated-orcid":false,"given":"Zhengang","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8525-3661","authenticated-orcid":false,"given":"Dan","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianchuan","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"crossref","DOI":"10.3390\/rs11111307","article-title":"Double-branch multi-attention mechanism network for hyperspectral image classification","volume":"11","author":"ma","year":"2019","journal-title":"Remote Sens"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/rs11020159","article-title":"Hyperspectral images classification based on dense convolutional networks with spectral-wise attention mechanism","volume":"11","author":"fang","year":"2019","journal-title":"Remote Sens"},{"key":"ref33","first-page":"2204","article-title":"Recurrent models of visual attention","author":"mnih","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref32","first-page":"1243","article-title":"Convolutional sequence to sequence learning,” Ser","volume":"70","author":"gehring","year":"2017"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2908756"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2755542"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2913372"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00326"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00081"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.601"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2886022"},{"key":"ref40","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"0","journal-title":"Proc 32nd Int Conf Mach Learn"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2907932"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2902568"},{"key":"ref13","first-page":"1","article-title":"Deep convolutional neural networks for hyperspectral image classification","author":"wei","year":"2015","journal-title":"J Sensors"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2017.2780890"},{"key":"ref15","first-page":"1","article-title":"Spectral-spatial classification of hyperspectral imagery with 3\ufffdd convolutional neural network","volume":"9","author":"ying","year":"2017","journal-title":"Remote Sens"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/rs11080963","article-title":"Spectral-spatial attention networks for hyperspectral image classification","volume":"11","author":"mei","year":"2019","journal-title":"Remote Sens"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2918080"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2967821"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2018.2830403"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2015.2488681"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2794326"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2019.09.006"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecoinf.2014.07.004"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2865953"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2646420"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SIU.2016.7495981"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2012.2216272"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"1579","DOI":"10.1109\/TGRS.2017.2765364","article-title":"Recent advances on spectral-spatial hyperspectral image classification: An overview and new guidelines","volume":"56","author":"lin","year":"2018","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2951160"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1111\/tgis.12164"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2636241"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2616355"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.434"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2018.2854840"},{"key":"ref41","first-page":"1","article-title":"Imagenet classification with deep convolutional neural networks","author":"alex","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref23","first-page":"171","article-title":"Dimensionally reduced features for hyperspectral image classification using deep learning","author":"charmisha","year":"0","journal-title":"Proc Int Conf Commun Cyber Phys Eng"},{"key":"ref44","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"Comput Sci"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2584107"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1080\/2150704X.2015.1047045"}],"container-title":["IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4609443\/9314330\/09376971.pdf?arnumber=9376971","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T11:56:27Z","timestamp":1643198187000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9376971\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/jstars.2021.3065706","relation":{},"ISSN":["1939-1404","2151-1535"],"issn-type":[{"value":"1939-1404","type":"print"},{"value":"2151-1535","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}