{"id":"https://openalex.org/W3209540366","doi":"https://doi.org/10.1109/tgrs.2021.3124913","title":"Convolutional Neural Networks for Multimodal Remote Sensing Data Classification","display_name":"Convolutional Neural Networks for Multimodal Remote Sensing Data Classification","publication_year":2021,"publication_date":"2021-11-02","ids":{"openalex":"https://openalex.org/W3209540366","doi":"https://doi.org/10.1109/tgrs.2021.3124913","mag":"3209540366"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3124913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3124913","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100761149","display_name":"Xin Wu","orcid":"https://orcid.org/0000-0002-1733-3560"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Wu","raw_affiliation_strings":["School of Information and Electronics and the Beijing Key Laboratory of Fractional Signals and Systems, Beijing Institute of Technology, Beijing, China","Beijing Institute of Technology"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics and the Beijing Key Laboratory of Fractional Signals and Systems, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075013625","display_name":"Danfeng Hong","orcid":"https://orcid.org/0000-0002-3212-9584"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danfeng Hong","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences [Beijing]"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences [Beijing]","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210149092","display_name":"Laboratoire Jean Kuntzmann","ror":"https://ror.org/04ett5b41","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210149092","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["CN","FR"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","LJK, INRIA, CNRS, Grenoble Institute of Technology (Grenoble INP), Universit\u00e9 Grenoble Alpes, Grenoble, France","Apprentissage de mod\u00e8les \u00e0 partir de donn\u00e9es massives","Chinese Academy of Sciences [Beijing]","GIPSA - Signal Images Physique"],"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"LJK, INRIA, CNRS, Grenoble Institute of Technology (Grenoble INP), Universit\u00e9 Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I899635006","https://openalex.org/I1326498283","https://openalex.org/I4210149092","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Apprentissage de mod\u00e8les \u00e0 partir de donn\u00e9es massives","institution_ids":[]},{"raw_affiliation_string":"Chinese Academy of Sciences [Beijing]","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"GIPSA - Signal Images Physique","institution_ids":["https://openalex.org/I4210124956"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100761149"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":29.9957,"has_fulltext":false,"cited_by_count":367,"citation_normalized_percentile":{"value":0.99809501,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9776999950408936,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9718999862670898,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8029100894927979},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6825705766677856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5768001675605774},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5667839050292969},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.5245447754859924},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4655004143714905},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4543262720108032},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.4269806444644928},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4093252420425415},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38997727632522583},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3582778573036194},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34163978695869446}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8029100894927979},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6825705766677856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5768001675605774},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5667839050292969},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.5245447754859924},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4655004143714905},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4543262720108032},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.4269806444644928},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4093252420425415},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38997727632522583},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3582778573036194},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34163978695869446},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2021.3124913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3124913","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:HAL:hal-03932903v1","is_oa":false,"landing_page_url":"https://hal.science/hal-03932903","pdf_url":null,"source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://ieeexplore.ieee.org/document/9598903","raw_type":"Journal articles"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3491711473","display_name":null,"funder_award_id":"2021M690385","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G6810561245","display_name":null,"funder_award_id":"62101045","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321048","display_name":"AXA Research Fund","ror":"https://ror.org/02zxqxw53"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1551648222","https://openalex.org/W1583106483","https://openalex.org/W1836465849","https://openalex.org/W2039097087","https://openalex.org/W2053154970","https://openalex.org/W2054689043","https://openalex.org/W2077570405","https://openalex.org/W2111787810","https://openalex.org/W2113513024","https://openalex.org/W2116699851","https://openalex.org/W2156808278","https://openalex.org/W2170535121","https://openalex.org/W2558661413","https://openalex.org/W2609880332","https://openalex.org/W2755992512","https://openalex.org/W2783165089","https://openalex.org/W2796684832","https://openalex.org/W2801230950","https://openalex.org/W2902746003","https://openalex.org/W2907147407","https://openalex.org/W2952565170","https://openalex.org/W2953303055","https://openalex.org/W2965945478","https://openalex.org/W2968707955","https://openalex.org/W2994639710","https://openalex.org/W2996478649","https://openalex.org/W2998030133","https://openalex.org/W3004480865","https://openalex.org/W3004968762","https://openalex.org/W3009883650","https://openalex.org/W3026303927","https://openalex.org/W3040988483","https://openalex.org/W3046027728","https://openalex.org/W3047443805","https://openalex.org/W3048631361","https://openalex.org/W3080185092","https://openalex.org/W3080263182","https://openalex.org/W3081753142","https://openalex.org/W3087984885","https://openalex.org/W3102692100","https://openalex.org/W3103294617","https://openalex.org/W3103695279","https://openalex.org/W3103812551","https://openalex.org/W3105298104","https://openalex.org/W3105997607","https://openalex.org/W3107721644","https://openalex.org/W3112751649","https://openalex.org/W3122774149","https://openalex.org/W3129857656","https://openalex.org/W3133902755","https://openalex.org/W3135445258","https://openalex.org/W3140885850","https://openalex.org/W3168367808","https://openalex.org/W3214821343","https://openalex.org/W6638667902","https://openalex.org/W6686207219","https://openalex.org/W6797691975"],"related_works":["https://openalex.org/W2783354812","https://openalex.org/W4384112194","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W4308259661","https://openalex.org/W4390813131","https://openalex.org/W2349383066","https://openalex.org/W4328132048","https://openalex.org/W2594043982","https://openalex.org/W3036493597"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"enormous":[3],"research":[4],"has":[5],"been":[6],"made":[7],"to":[8,45],"improve":[9],"the":[10,21,48,84,99,102,136,148,152,157,183],"classification":[11,168],"performance":[12],"of":[13,24,37,93,101,156,185],"single-modal":[14],"remote":[15],"sensing":[16],"(RS)":[17],"data.":[18],"However,":[19],"with":[20,75,162],"ever-growing":[22],"availability":[23],"RS":[25,39,49,62,95,123,166],"data":[26,40,63,96,167],"acquired":[27],"from":[28],"satellite":[29],"or":[30],"airborne":[31],"platforms,":[32],"simultaneous":[33],"processing":[34],"and":[35,128,131,139,141,154,175],"analysis":[36],"multimodal":[38,61,122,165],"pose":[41],"a":[42,56,73,113],"new":[43,58],"challenge":[44],"researchers":[46],"in":[47,112,160],"community.":[50],"To":[51],"this":[52],"end,":[53],"we":[54],"propose":[55],"deep-learning-based":[57],"framework":[59],"for":[60,182],"classification,":[64],"where":[65],"convolutional":[66],"neural":[67],"networks":[68],"(CNNs)":[69],"are":[70],"taken":[71],"as":[72],"backbone":[74],"an":[76],"advanced":[77],"cross-channel":[78],"reconstruction":[79,103],"module,":[80],"called":[81],"CCR-Net.":[82],"As":[83],"name":[85],"suggests,":[86],"CCR-Net":[87,159],"learns":[88],"more":[89,114],"compact":[90],"fusion":[91],"representations":[92],"different":[94],"sources":[97],"by":[98],"means":[100],"strategy":[104],"across":[105],"modalities":[106],"that":[107],"can":[108],"mutually":[109],"exchange":[110],"information":[111],"effective":[115],"way.":[116],"Extensive":[117],"experiments":[118],"conducted":[119],"on":[120],"two":[121],"datasets,":[124],"including":[125],"hyperspectral":[126],"(HS)":[127],"light":[129],"detection":[130],"ranging":[132],"(LiDAR)":[133],"data,":[134,146],"i.e.,":[135,147],"Houston2013":[137],"dataset,":[138,150],"HS":[140],"synthetic":[142],"aperture":[143],"radar":[144],"(SAR)":[145],"Berlin":[149],"demonstrate":[151],"effectiveness":[153],"superiority":[155],"proposed":[158],"comparison":[161],"several":[163],"state-of-the-art":[164],"methods.":[169],"The":[170],"codes":[171],"will":[172],"be":[173],"openly":[174],"freely":[176],"available":[177],"at":[178],"<uri":[179],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[180],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/danfenghong/IEEE_TGRS_CCR-Net</uri>":[181],"sake":[184],"reproducibility.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":121},{"year":2024,"cited_by_count":107},{"year":2023,"cited_by_count":87},{"year":2022,"cited_by_count":44}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}