{"id":"https://openalex.org/W2942454403","doi":"https://doi.org/10.1109/tgrs.2019.2907932","title":"Deep Learning for Hyperspectral Image Classification: An Overview","display_name":"Deep Learning for Hyperspectral Image Classification: An Overview","publication_year":2019,"publication_date":"2019-04-27","ids":{"openalex":"https://openalex.org/W2942454403","doi":"https://doi.org/10.1109/tgrs.2019.2907932","mag":"2942454403"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2019.2907932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2907932","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.12861","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shutao Li","orcid":"https://orcid.org/0000-0002-0585-9848"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shutao Li","raw_affiliation_strings":["Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Weiwei Song","orcid":"https://orcid.org/0000-0001-5089-4127"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weiwei Song","raw_affiliation_strings":["Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Leyuan Fang","orcid":"https://orcid.org/0000-0003-2351-4461"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leyuan Fang","raw_affiliation_strings":["Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yushi Chen","orcid":"https://orcid.org/0000-0003-2421-0996"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yushi Chen","raw_affiliation_strings":["Department of Information Engineering, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Pedram Ghamisi","orcid":"https://orcid.org/0000-0003-1203-741X"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Pedram Ghamisi","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology (HIF), Exploration, Freiberg, Germany"],"affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology (HIF), Exploration, Freiberg, Germany","institution_ids":["https://openalex.org/I4210148560","https://openalex.org/I2801798921"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jon Atli Benediktsson","orcid":"https://orcid.org/0000-0003-0621-9647"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Jon Atli Benediktsson","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavk, Iceland"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavk, Iceland","institution_ids":["https://openalex.org/I165368041"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":114.5861,"has_fulltext":false,"cited_by_count":1747,"citation_normalized_percentile":{"value":0.99994322,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"57","issue":"9","first_page":"6690","last_page":"6709"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9020000100135803,"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":0.9020000100135803,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.0034000000450760126,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13748","display_name":"Advanced Statistical Modeling Techniques","score":0.0032999999821186066,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.90829998254776},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.8888999819755554},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6093999743461609},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.49320000410079956},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4287000000476837},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3944000005722046},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.37119999527931213},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.36309999227523804}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.90829998254776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.8888999819755554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7997999787330627},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7871999740600586},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6093999743461609},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5432000160217285},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.49320000410079956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.36309999227523804},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.3400000035762787},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3158000111579895},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.298799991607666},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2964000105857849},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2019.2907932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2907932","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:arXiv.org:1910.12861","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.12861","pdf_url":"https://arxiv.org/pdf/1910.12861","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1910.12861","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.12861","pdf_url":"https://arxiv.org/pdf/1910.12861","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2027762821","display_name":null,"funder_award_id":"61890962","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3693646142","display_name":null,"funder_award_id":"61771192","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8651560819","display_name":null,"funder_award_id":"2018YFB1305200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G898426514","display_name":null,"funder_award_id":"61520106001","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":112,"referenced_works":["https://openalex.org/W248389711","https://openalex.org/W1521436688","https://openalex.org/W1903029394","https://openalex.org/W1939429412","https://openalex.org/W1950365613","https://openalex.org/W1966580635","https://openalex.org/W1972085588","https://openalex.org/W1990895816","https://openalex.org/W1998030734","https://openalex.org/W2004104348","https://openalex.org/W2016589492","https://openalex.org/W2029316659","https://openalex.org/W2045095960","https://openalex.org/W2052160904","https://openalex.org/W2058795991","https://openalex.org/W2059089906","https://openalex.org/W2064675550","https://openalex.org/W2090424610","https://openalex.org/W2097117768","https://openalex.org/W2097915756","https://openalex.org/W2098676252","https://openalex.org/W2102605133","https://openalex.org/W2103094532","https://openalex.org/W2107878631","https://openalex.org/W2113464037","https://openalex.org/W2114819256","https://openalex.org/W2136251662","https://openalex.org/W2140340527","https://openalex.org/W2144151128","https://openalex.org/W2153635508","https://openalex.org/W2158400785","https://openalex.org/W2162698522","https://openalex.org/W2164330327","https://openalex.org/W2166923144","https://openalex.org/W2179290474","https://openalex.org/W2194775991","https://openalex.org/W2248723555","https://openalex.org/W2257669061","https://openalex.org/W2276858186","https://openalex.org/W2289977264","https://openalex.org/W2314785379","https://openalex.org/W2345128667","https://openalex.org/W2412588858","https://openalex.org/W2500751094","https://openalex.org/W2518831014","https://openalex.org/W2518897583","https://openalex.org/W2527650001","https://openalex.org/W2547846938","https://openalex.org/W2548791488","https://openalex.org/W2558391528","https://openalex.org/W2560523472","https://openalex.org/W2565258258","https://openalex.org/W2572303978","https://openalex.org/W2582369608","https://openalex.org/W2587790406","https://openalex.org/W2592224809","https://openalex.org/W2595902385","https://openalex.org/W2600746131","https://openalex.org/W2603422184","https://openalex.org/W2603834682","https://openalex.org/W2609880332","https://openalex.org/W2611452721","https://openalex.org/W2611655888","https://openalex.org/W2613575128","https://openalex.org/W2614256707","https://openalex.org/W2614326984","https://openalex.org/W2623518586","https://openalex.org/W2625436554","https://openalex.org/W2732412926","https://openalex.org/W2737996023","https://openalex.org/W2757208835","https://openalex.org/W2764034829","https://openalex.org/W2764276316","https://openalex.org/W2765739551","https://openalex.org/W2765923665","https://openalex.org/W2766947113","https://openalex.org/W2767651786","https://openalex.org/W2767805377","https://openalex.org/W2768211636","https://openalex.org/W2768309288","https://openalex.org/W2768537477","https://openalex.org/W2768975974","https://openalex.org/W2772452219","https://openalex.org/W2773213684","https://openalex.org/W2777427437","https://openalex.org/W2779530678","https://openalex.org/W2782517596","https://openalex.org/W2784118841","https://openalex.org/W2789643644","https://openalex.org/W2791006446","https://openalex.org/W2792332881","https://openalex.org/W2799390666","https://openalex.org/W2803704927","https://openalex.org/W2804532080","https://openalex.org/W2804744787","https://openalex.org/W2804902458","https://openalex.org/W2808098982","https://openalex.org/W2809113079","https://openalex.org/W2809635958","https://openalex.org/W2887785636","https://openalex.org/W2888119354","https://openalex.org/W2889861425","https://openalex.org/W2894165434","https://openalex.org/W2898381489","https://openalex.org/W2900116731","https://openalex.org/W2919115771","https://openalex.org/W2922379874","https://openalex.org/W4240485910","https://openalex.org/W6635815790","https://openalex.org/W6682132143","https://openalex.org/W6684191040","https://openalex.org/W6743446608"],"related_works":[],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1,81],"(HSI)":[2],"classification":[3,26,113,131,217,235],"has":[4,61,91],"become":[5],"a":[6,65,78,106,157,206],"hot":[7],"topic":[8],"in":[9,77,178,192,242],"the":[10,17,24,48,53,126,145,161,175,186,193],"field":[11,196],"of":[12,20,27,80,109,129,147,209],"remote":[13,194],"sensing.":[14],"In":[15,36,56,183],"general,":[16],"complex":[18],"characteristics":[19],"hyperspectral":[21,38],"data":[22,29],"make":[23],"accurate":[25],"such":[28],"challenging":[30],"for":[31,119,224],"traditional":[32,138],"machine":[33,139],"learning":[34,60,90,140,149],"methods.":[35],"addition,":[37,184],"imaging":[39],"often":[40],"deals":[41],"with":[42],"an":[43],"inherently":[44],"nonlinear":[45,72],"relation":[46],"between":[47],"captured":[49],"spectral":[50],"information":[51],"and":[52,74,98,115,142,169,201],"corresponding":[54,162],"materials.":[55],"recent":[57,176],"years,":[58],"deep":[59,89,110,148,179,203,233],"been":[62,93],"recognized":[63],"as":[64],"powerful":[66],"feature-extraction":[67],"tool":[68],"to":[69,95,150,172,215],"effectively":[70,135],"address":[71],"problems":[73],"widely":[75],"used":[76],"number":[79,208],"processing":[82],"tasks.":[83],"Motivated":[84],"by":[85,137],"those":[86],"successful":[87],"applications,":[88],"also":[92,143],"introduced":[94],"classify":[96],"HSIs":[97,241],"demonstrated":[99],"good":[100],"performance.":[101],"This":[102],"survey":[103],"paper":[104],"presents":[105],"systematic":[107],"review":[108,174],"learning-based":[111,180,234],"HSI":[112,130,181],"literatures":[114],"compares":[116],"several":[117,231],"strategies":[118,214],"this":[120,228],"topic.":[121,229],"Specifically,":[122],"we":[123,155,211],"first":[124],"summarize":[125],"main":[127],"challenges":[128],"which":[132,219],"cannot":[133],"be":[134],"overcome":[136],"methods,":[141],"introduce":[144],"advantages":[146],"handle":[151],"these":[152],"problems.":[153],"Then,":[154],"build":[156],"framework":[158],"that":[159,188],"divides":[160],"works":[163],"into":[164],"spectral-feature":[165],"networks,":[166,168],"spatial-feature":[167],"spectral-spatial-feature":[170],"networks":[171,204],"systematically":[173],"achievements":[177],"classification.":[182],"considering":[185],"fact":[187],"available":[189],"training":[190,202],"samples":[191],"sensing":[195],"are":[197,237],"usually":[198],"very":[199],"limited":[200],"require":[205],"large":[207],"samples,":[210],"include":[212],"some":[213,222],"improve":[216],"performance,":[218],"can":[220],"provide":[221],"guidelines":[223],"future":[225],"studies":[226],"on":[227,239],"Finally,":[230],"representative":[232],"methods":[236],"conducted":[238],"real":[240],"our":[243],"experiments.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":61},{"year":2025,"cited_by_count":339},{"year":2024,"cited_by_count":396},{"year":2023,"cited_by_count":319},{"year":2022,"cited_by_count":275},{"year":2021,"cited_by_count":214},{"year":2020,"cited_by_count":133},{"year":2019,"cited_by_count":10}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2019-05-03T00:00:00"}