{"id":"https://openalex.org/W3128861763","doi":"https://doi.org/10.1109/tgrs.2021.3052048","title":"Generative Adversarial Minority Oversampling for Spectral\u2013Spatial Hyperspectral Image Classification","display_name":"Generative Adversarial Minority Oversampling for Spectral\u2013Spatial Hyperspectral Image Classification","publication_year":2021,"publication_date":"2021-02-05","ids":{"openalex":"https://openalex.org/W3128861763","doi":"https://doi.org/10.1109/tgrs.2021.3052048","mag":"3128861763"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3052048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3052048","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/A5087427076","display_name":"Swalpa Kumar Roy","orcid":"https://orcid.org/0000-0002-6580-3977"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Swalpa Kumar Roy","raw_affiliation_strings":["Computer Science and Engineering Department, Jalpaiguri Government Engineering College, Jalpaiguri, India"],"raw_orcid":"https://orcid.org/0000-0002-6580-3977","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, Jalpaiguri Government Engineering College, Jalpaiguri, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039673511","display_name":"Juan M. Haut","orcid":"https://orcid.org/0000-0001-6701-961X"},"institutions":[{"id":"https://openalex.org/I178450904","display_name":"Universidad Nacional de Educaci\u00f3n a Distancia","ror":"https://ror.org/02msb5n36","country_code":"ES","type":"education","lineage":["https://openalex.org/I178450904"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan M. Haut","raw_affiliation_strings":["Department of Communication and Control Systems, National Distance Education University, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0001-6701-961X","affiliations":[{"raw_affiliation_string":"Department of Communication and Control Systems, National Distance Education University, Madrid, Spain","institution_ids":["https://openalex.org/I178450904"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046123228","display_name":"Mercedes E. Paoletti","orcid":"https://orcid.org/0000-0003-1030-3729"},"institutions":[{"id":"https://openalex.org/I82767444","display_name":"Universidad de M\u00e1laga","ror":"https://ror.org/036b2ww28","country_code":"ES","type":"education","lineage":["https://openalex.org/I82767444"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Mercedes E. Paoletti","raw_affiliation_strings":["Department of Computer Architecture, School of Computer Science and Engineering, University of M\u00e1laga, M\u00e1laga, Spain"],"raw_orcid":"https://orcid.org/0000-0003-1030-3729","affiliations":[{"raw_affiliation_string":"Department of Computer Architecture, School of Computer Science and Engineering, University of M\u00e1laga, M\u00e1laga, Spain","institution_ids":["https://openalex.org/I82767444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048082929","display_name":"Shiv Ram Dubey","orcid":"https://orcid.org/0000-0002-4532-8996"},"institutions":[{"id":"https://openalex.org/I26072440","display_name":"Indian Institute of Information Technology Allahabad","ror":"https://ror.org/03rgjt374","country_code":"IN","type":"education","lineage":["https://openalex.org/I26072440"]},{"id":"https://openalex.org/I4387155292","display_name":"Indian Institute of Information Technology Sri City","ror":"https://ror.org/026873d40","country_code":null,"type":"education","lineage":["https://openalex.org/I4387155292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shiv Ram Dubey","raw_affiliation_strings":["Computer Vision Group, Indian Institute of Information Technology, Sri City, India"],"raw_orcid":"https://orcid.org/0000-0002-4532-8996","affiliations":[{"raw_affiliation_string":"Computer Vision Group, Indian Institute of Information Technology, Sri City, India","institution_ids":["https://openalex.org/I26072440","https://openalex.org/I4387155292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054292278","display_name":"Antonio Plaza","orcid":"https://orcid.org/0000-0002-9613-1659"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Plaza","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"raw_orcid":"https://orcid.org/0000-0002-9613-1659","affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.4678,"has_fulltext":false,"cited_by_count":93,"citation_normalized_percentile":{"value":0.98321882,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"15"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.982200026512146,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/oversampling","display_name":"Oversampling","score":0.839735746383667},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.744928777217865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7361265420913696},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7096225619316101},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6808779835700989},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.575753390789032},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5563313364982605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5534908771514893},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.5191168785095215},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49012526869773865},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.46886852383613586},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.37098953127861023},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35936108231544495},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.07492506504058838}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.839735746383667},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.744928777217865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7361265420913696},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7096225619316101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6808779835700989},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.575753390789032},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5563313364982605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5534908771514893},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.5191168785095215},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49012526869773865},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.46886852383613586},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37098953127861023},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35936108231544495},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.07492506504058838},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2021.3052048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3052048","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6800000071525574}],"awards":[],"funders":[{"id":"https://openalex.org/F4320328352","display_name":"Junta de Extremadura","ror":"https://ror.org/01df4mv68"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1541950099","https://openalex.org/W1966580635","https://openalex.org/W1982427174","https://openalex.org/W2000563363","https://openalex.org/W2022470997","https://openalex.org/W2040181375","https://openalex.org/W2040387238","https://openalex.org/W2041100636","https://openalex.org/W2097915756","https://openalex.org/W2099471712","https://openalex.org/W2101711129","https://openalex.org/W2104269704","https://openalex.org/W2114828048","https://openalex.org/W2118978333","https://openalex.org/W2119498311","https://openalex.org/W2136251662","https://openalex.org/W2164330327","https://openalex.org/W2185967890","https://openalex.org/W2194775991","https://openalex.org/W2519653196","https://openalex.org/W2548791488","https://openalex.org/W2735835382","https://openalex.org/W2743255627","https://openalex.org/W2764276316","https://openalex.org/W2772452219","https://openalex.org/W2777427437","https://openalex.org/W2791006446","https://openalex.org/W2792332881","https://openalex.org/W2793607269","https://openalex.org/W2793941577","https://openalex.org/W2794472454","https://openalex.org/W2795061970","https://openalex.org/W2808098982","https://openalex.org/W2809113079","https://openalex.org/W2809635958","https://openalex.org/W2887785636","https://openalex.org/W2888119354","https://openalex.org/W2892075618","https://openalex.org/W2896847173","https://openalex.org/W2898381489","https://openalex.org/W2900614378","https://openalex.org/W2908955282","https://openalex.org/W2914331134","https://openalex.org/W2919115771","https://openalex.org/W2921445432","https://openalex.org/W2940678725","https://openalex.org/W2944413439","https://openalex.org/W2944653015","https://openalex.org/W2950266692","https://openalex.org/W2953926847","https://openalex.org/W2964199361","https://openalex.org/W2970175774","https://openalex.org/W2981515171","https://openalex.org/W2988047368","https://openalex.org/W2990257819","https://openalex.org/W2991616716","https://openalex.org/W2994050370","https://openalex.org/W2995709945","https://openalex.org/W2997343747","https://openalex.org/W3000573080","https://openalex.org/W3003552243","https://openalex.org/W3004877455","https://openalex.org/W3004925702","https://openalex.org/W3006462480","https://openalex.org/W3006984222","https://openalex.org/W3007076381","https://openalex.org/W3010700973","https://openalex.org/W3011645114","https://openalex.org/W3025719176","https://openalex.org/W3037409780","https://openalex.org/W3105357426","https://openalex.org/W6631190155","https://openalex.org/W6636749155","https://openalex.org/W6729482032","https://openalex.org/W6732491067","https://openalex.org/W6766480550"],"related_works":["https://openalex.org/W2995777218","https://openalex.org/W3217069185","https://openalex.org/W2784931967","https://openalex.org/W4293400715","https://openalex.org/W3049340819","https://openalex.org/W4308928038","https://openalex.org/W4200430540","https://openalex.org/W3141413246","https://openalex.org/W3112293331","https://openalex.org/W2808862658"],"abstract_inverted_index":{"Recently,":[0],"convolutional":[1],"neural":[2],"networks":[3],"(CNNs)":[4],"have":[5,46,229],"exhibited":[6],"commendable":[7],"performance":[8,55,201,251],"for":[9,22,70,109],"hyperspectral":[10,132],"image":[11],"(HSI)":[12],"classification.":[13,83],"Generally,":[14],"an":[15],"important":[16],"number":[17],"of":[18,56,78,119,129,164,190,202,223],"samples":[19,48,69,108,118,123,159,167],"are":[20,124,176],"needed":[21],"each":[23],"class":[24,38],"to":[25,49,160,168,185],"properly":[26],"train":[27],"CNNs.":[28],"However,":[29],"existing":[30,57,117],"HSI":[31,82,211],"data":[32,80,175,183,212,240,255],"sets":[33],"suffer":[34],"from":[35,137],"a":[36,86,130],"significant":[37],"imbalance":[39],"problem,":[40],"where":[41],"many":[42],"classes":[43,111,163],"do":[44],"not":[45],"enough":[47],"characterize":[50],"the":[51,63,71,116,127,138,141,146,162,180,187,191,194,200,203,206,244,249,253],"spectral":[52],"information.":[53],"The":[54,100,122,173,235,257],"CNN":[58],"models":[59],"is":[60,92,143,152,260],"biased":[61],"toward":[62],"majority":[64],"classes,":[65],"which":[66,94,151,169,246],"possess":[67],"more":[68,107],"training.":[72],"This":[73],"article":[74],"addresses":[75],"this":[76],"issue":[77],"imbalanced":[79],"in":[81,126,145,232],"In":[84],"particular,":[85],"new":[87],"<monospace":[88,102,147],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[89,103,148,265],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">3D-HyperGAMO</monospace>":[90,104,149],"model":[91,204,237],"proposed,":[93],"uses":[95],"generative":[96],"adversarial":[97],"minority":[98,110],"oversampling.":[99],"proposed":[101,236],"automatically":[105],"generates":[106],"at":[112,263],"training":[113,182],"time,":[114],"using":[115,154,205],"that":[120],"class.":[121,192],"generated":[125,158,166,174],"form":[128],"3-D":[131,196],"patch.":[133],"A":[134],"different":[135],"classifier":[136,197],"generator":[139],"and":[140,157,226],"discriminator":[142],"used":[144],"model,":[150],"trained":[153,195],"both":[155],"original":[156,181],"determine":[161],"newly":[165],"they":[170],"actually":[171],"belong.":[172],"combined":[177],"classwise":[178],"with":[179],"set":[184],"learn":[186],"network":[188,198],"parameters":[189],"Finally,":[193],"validates":[199],"test":[207],"set.":[208],"Four":[209],"benchmark":[210],"sets,":[213],"namely,":[214],"Indian":[215],"Pines":[216],"(IP),":[217],"Kennedy":[218],"Space":[219],"Center":[220],"(KSC),":[221],"University":[222],"Pavia":[224],"(UP),":[225],"Botswana":[227],"(BW),":[228],"been":[230],"considered":[231,254],"our":[233],"experiments.":[234],"shows":[238],"outstanding":[239],"generation":[241],"ability":[242],"during":[243],"training,":[245],"significantly":[247],"improves":[248],"classification":[250],"over":[252],"sets.":[256],"source":[258],"code":[259],"available":[261],"publicly":[262],"<uri":[264],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/mhaut/3D-HyperGAMO</uri>":[266],".":[267]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":26},{"year":2021,"cited_by_count":11}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
