{"id":"https://openalex.org/W3114720220","doi":"https://doi.org/10.1109/tgrs.2020.3043267","title":"Attention-Based Adaptive Spectral\u2013Spatial Kernel ResNet for Hyperspectral Image Classification","display_name":"Attention-Based Adaptive Spectral\u2013Spatial Kernel ResNet for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-12-24","ids":{"openalex":"https://openalex.org/W3114720220","doi":"https://doi.org/10.1109/tgrs.2020.3043267","mag":"3114720220"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.3043267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3043267","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://iris.unitn.it/bitstream/11572/401505/3/Attention-Based-Adaptive-Spectral-Spatial-Kernel-ResNet-for-Hyperspectral-Image-Classification-2-14.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087427076","display_name":"Swalpa Kumar Roy","orcid":"https://orcid.org/0000-0002-6580-3977"},"institutions":[{"id":"https://openalex.org/I4210098857","display_name":"Government of Himachal Pradesh","ror":"https://ror.org/013bmyp84","country_code":"IN","type":"government","lineage":["https://openalex.org/I4210098857"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Swalpa Kumar Roy","raw_affiliation_strings":["Jalpaiguri Government Engineering College, Jalpaiguri, India"],"raw_orcid":"https://orcid.org/0000-0002-6580-3977","affiliations":[{"raw_affiliation_string":"Jalpaiguri Government Engineering College, Jalpaiguri, India","institution_ids":["https://openalex.org/I4210098857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018762168","display_name":"Suvojit Manna","orcid":"https://orcid.org/0000-0003-2540-3204"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Suvojit Manna","raw_affiliation_strings":["CureSkin, Bengaluru, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CureSkin, Bengaluru, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010200502","display_name":"Tiecheng Song","orcid":"https://orcid.org/0000-0003-1264-2812"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiecheng Song","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-1264-2812","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006095323","display_name":"Lorenzo Bruzzone","orcid":"https://orcid.org/0000-0002-6036-459X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lorenzo Bruzzone","raw_affiliation_strings":["Remote Sensing Laboratory, University of Trento, Trento, Italy"],"raw_orcid":"https://orcid.org/0000-0002-6036-459X","affiliations":[{"raw_affiliation_string":"Remote Sensing Laboratory, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":23.4522,"has_fulltext":true,"cited_by_count":494,"citation_normalized_percentile":{"value":0.99741706,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"59","issue":"9","first_page":"7831","last_page":"7843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7953203916549683},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7079393267631531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6810532808303833},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6342214345932007},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6279534101486206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6261018514633179},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5821461081504822},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4211360812187195},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2182321846485138},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07073411345481873},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06687596440315247}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7953203916549683},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7079393267631531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6810532808303833},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6342214345932007},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6279534101486206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6261018514633179},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5821461081504822},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4211360812187195},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2182321846485138},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07073411345481873},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06687596440315247}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2020.3043267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3043267","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:iris.unitn.it:11572/401505","is_oa":true,"landing_page_url":"https://hdl.handle.net/11572/401505","pdf_url":"https://iris.unitn.it/bitstream/11572/401505/3/Attention-Based-Adaptive-Spectral-Spatial-Kernel-ResNet-for-Hyperspectral-Image-Classification-2-14.pdf","source":{"id":"https://openalex.org/S4377196320","display_name":"Iris (University of Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:iris.unitn.it:11572/401505","is_oa":true,"landing_page_url":"https://hdl.handle.net/11572/401505","pdf_url":"https://iris.unitn.it/bitstream/11572/401505/3/Attention-Based-Adaptive-Spectral-Spatial-Kernel-ResNet-for-Hyperspectral-Image-Classification-2-14.pdf","source":{"id":"https://openalex.org/S4377196320","display_name":"Iris (University of Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G1270112442","display_name":null,"funder_award_id":"61702065","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G159667453","display_name":null,"funder_award_id":"cstc2018jcyjAX0033","funder_id":"https://openalex.org/F4320327865","funder_display_name":"Chongqing Research Program of Basic Research and Frontier Technology"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327865","display_name":"Chongqing Research Program of Basic Research and Frontier Technology","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3114720220.pdf","grobid_xml":"https://content.openalex.org/works/W3114720220.grobid-xml"},"referenced_works_count":96,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1665214252","https://openalex.org/W1686810756","https://openalex.org/W1966580635","https://openalex.org/W1982427174","https://openalex.org/W1990653740","https://openalex.org/W2018257962","https://openalex.org/W2022470997","https://openalex.org/W2029316659","https://openalex.org/W2046005667","https://openalex.org/W2101711129","https://openalex.org/W2106869737","https://openalex.org/W2136251662","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2302255633","https://openalex.org/W2401231614","https://openalex.org/W2500751094","https://openalex.org/W2522078899","https://openalex.org/W2550553598","https://openalex.org/W2556967412","https://openalex.org/W2588023376","https://openalex.org/W2614256707","https://openalex.org/W2614326984","https://openalex.org/W2743255627","https://openalex.org/W2752782242","https://openalex.org/W2755992512","https://openalex.org/W2762629333","https://openalex.org/W2764276316","https://openalex.org/W2767887540","https://openalex.org/W2774466993","https://openalex.org/W2792332881","https://openalex.org/W2793941577","https://openalex.org/W2795247881","https://openalex.org/W2808098982","https://openalex.org/W2884585870","https://openalex.org/W2885785305","https://openalex.org/W2888119354","https://openalex.org/W2889456682","https://openalex.org/W2895634443","https://openalex.org/W2896847173","https://openalex.org/W2898381489","https://openalex.org/W2901461790","https://openalex.org/W2912961521","https://openalex.org/W2914281074","https://openalex.org/W2914331134","https://openalex.org/W2915090373","https://openalex.org/W2921599942","https://openalex.org/W2922379874","https://openalex.org/W2922509574","https://openalex.org/W2937638900","https://openalex.org/W2941141441","https://openalex.org/W2942454403","https://openalex.org/W2949846184","https://openalex.org/W2955058313","https://openalex.org/W2962702700","https://openalex.org/W2962770389","https://openalex.org/W2962971773","https://openalex.org/W2963420686","https://openalex.org/W2963495494","https://openalex.org/W2964121744","https://openalex.org/W2964137095","https://openalex.org/W2964199361","https://openalex.org/W2991616716","https://openalex.org/W3003552243","https://openalex.org/W3004877455","https://openalex.org/W3014628500","https://openalex.org/W3015356365","https://openalex.org/W3025719176","https://openalex.org/W3031696400","https://openalex.org/W3034552520","https://openalex.org/W3046476394","https://openalex.org/W3047443805","https://openalex.org/W3048631361","https://openalex.org/W3049737467","https://openalex.org/W3066454894","https://openalex.org/W3098388691","https://openalex.org/W3100011500","https://openalex.org/W3100714546","https://openalex.org/W3101012758","https://openalex.org/W3102692100","https://openalex.org/W3103092912","https://openalex.org/W3103695279","https://openalex.org/W3103753223","https://openalex.org/W3105005050","https://openalex.org/W3105357426","https://openalex.org/W3122774149","https://openalex.org/W3162474807","https://openalex.org/W4241152325","https://openalex.org/W6631190155","https://openalex.org/W6637242042","https://openalex.org/W6637373629","https://openalex.org/W6676194229","https://openalex.org/W6729983426","https://openalex.org/W6749845547","https://openalex.org/W6768952390"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W3034864990"],"abstract_inverted_index":{"Hyperspectral":[0],"images":[1],"(HSIs)":[2],"provide":[3,172],"rich":[4],"spectral-spatial":[5,26,82,102,125],"information":[6],"with":[7,42,96,188],"stacked":[8],"hundreds":[9],"of":[10,17,24,178],"contiguous":[11],"narrowbands.":[12],"Due":[13],"to":[14,55,70,99,122,139],"the":[15,22,72,114,141,160,189],"existence":[16],"noise":[18],"and":[19,60,65,131,157,159,185],"band":[20],"correlation,":[21],"selection":[23],"informative":[25],"kernel":[27,83],"features":[28,103,126],"poses":[29],"a":[30],"challenge.":[31],"This":[32],"is":[33],"often":[34],"addressed":[35],"by":[36],"using":[37,127],"convolutional":[38,120],"neural":[39],"networks":[40],"(CNNs)":[41],"receptive":[43],"field":[44],"(RF)":[45],"having":[46],"fixed":[47],"sizes.":[48],"However,":[49],"these":[50],"solutions":[51],"cannot":[52],"enable":[53],"neurons":[54],"effectively":[56],"adjust":[57],"RF":[58],"sizes":[59],"cross-channel":[61],"dependencies":[62],"when":[63],"forward":[64],"backward":[66],"propagations":[67],"are":[68,146],"used":[69],"optimize":[71],"network.":[73],"In":[74,112],"this":[75],"article,":[76],"we":[77],"present":[78],"an":[79,108,133],"attention-based":[80],"adaptive":[81],"improved":[84,128],"residual":[85],"network":[86,116],"(A":[87],"<sup":[88,92,163,167],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[89,93,164,168],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[90,94,165,169],"S":[91,166],"K-ResNet)":[95],"spectral":[97],"attention":[98],"capture":[100],"discriminative":[101],"for":[104],"HSI":[105],"classification":[106,142,174],"in":[107,176],"end-to-end":[109],"training":[110],"fashion.":[111],"particular,":[113],"proposed":[115,161],"learns":[117],"selective":[118],"3-D":[119,129],"kernels":[121],"jointly":[123],"extract":[124],"ResBlocks":[130],"adopts":[132],"efficient":[134],"feature":[135],"recalibration":[136],"(EFR)":[137],"mechanism":[138],"boost":[140],"performance.":[143],"Extensive":[144],"experiments":[145],"performed":[147],"on":[148],"three":[149],"well-known":[150],"hyperspectral":[151],"data":[152],"sets,":[153],"i.e.,":[154],"IP,":[155],"KSC,":[156],"UP,":[158],"A":[162],"K-ResNet":[170],"can":[171],"better":[173],"results":[175],"terms":[177],"overall":[179],"accuracy":[180,183],"(OA),":[181],"average":[182],"(AA),":[184],"Kappa":[186],"compared":[187],"existing":[190],"methods":[191],"investigated.":[192],"The":[193],"source":[194],"code":[195],"will":[196],"be":[197],"made":[198],"available":[199],"at":[200],"https://github.com/suvojit-":[201],"0\u00d755aa/A2S2K-ResNet.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":36},{"year":2025,"cited_by_count":122},{"year":2024,"cited_by_count":125},{"year":2023,"cited_by_count":117},{"year":2022,"cited_by_count":75},{"year":2021,"cited_by_count":19}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2021-01-05T00:00:00"}
