{"id":"https://openalex.org/W2029766222","doi":"https://doi.org/10.1109/jstars.2013.2251969","title":"Combining Multiple Classification Methods for Hyperspectral Data Interpretation","display_name":"Combining Multiple Classification Methods for Hyperspectral Data Interpretation","publication_year":2013,"publication_date":"2013-03-29","ids":{"openalex":"https://openalex.org/W2029766222","doi":"https://doi.org/10.1109/jstars.2013.2251969","mag":"2029766222"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2013.2251969","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2013.2251969","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5110246905","display_name":"Andrey Bicalho Santos","orcid":"https://orcid.org/0000-0002-0785-6202"},"institutions":[{"id":"https://openalex.org/I110200422","display_name":"Universidade Federal de Minas Gerais","ror":"https://ror.org/0176yjw32","country_code":"BR","type":"education","lineage":["https://openalex.org/I110200422"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Andrey Bicalho Santos","raw_affiliation_strings":["Computer Science Department, Federal University of Minas Gerais, Belo Horizonte, Brazil","Comput. Sci. Dept., Fed. Univ. of Minas Gerais, Belo Horizonte, Brazil#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Federal University of Minas Gerais, Belo Horizonte, Brazil","institution_ids":["https://openalex.org/I110200422"]},{"raw_affiliation_string":"Comput. Sci. Dept., Fed. Univ. of Minas Gerais, Belo Horizonte, Brazil#TAB#","institution_ids":["https://openalex.org/I110200422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103622466","display_name":"Arnaldo de Albuquerque Ara\u00fajo","orcid":"https://orcid.org/0009-0003-7254-2001"},"institutions":[{"id":"https://openalex.org/I110200422","display_name":"Universidade Federal de Minas Gerais","ror":"https://ror.org/0176yjw32","country_code":"BR","type":"education","lineage":["https://openalex.org/I110200422"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Arnaldo de Albuquerque Araujo","raw_affiliation_strings":["Computer Science Department, Federal University of Minas Gerais, Belo Horizonte, Brazil","Comput. Sci. Dept., Fed. Univ. of Minas Gerais, Belo Horizonte, Brazil#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Federal University of Minas Gerais, Belo Horizonte, Brazil","institution_ids":["https://openalex.org/I110200422"]},{"raw_affiliation_string":"Comput. Sci. Dept., Fed. Univ. of Minas Gerais, Belo Horizonte, Brazil#TAB#","institution_ids":["https://openalex.org/I110200422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033489756","display_name":"David Menotti","orcid":"https://orcid.org/0000-0003-2430-2030"},"institutions":[{"id":"https://openalex.org/I10824318","display_name":"Universidade Federal de Ouro Preto","ror":"https://ror.org/056s65p46","country_code":"BR","type":"education","lineage":["https://openalex.org/I10824318"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"David Menotti","raw_affiliation_strings":["Computing Department, Federal University of Ouro Preto, Preto, Brazil","Comput. Dept., Fed. Univ. of Ouro Preto, Ouro Preto, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computing Department, Federal University of Ouro Preto, Preto, Brazil","institution_ids":["https://openalex.org/I10824318"]},{"raw_affiliation_string":"Comput. Dept., Fed. Univ. of Ouro Preto, Ouro Preto, Brazil","institution_ids":["https://openalex.org/I10824318"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":null,"fwci":10.1165,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.98173958,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"6","issue":"3","first_page":"1450","last_page":"1459"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9945999979972839,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9438999891281128,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8807091116905212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7599695324897766},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6145661473274231},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6086733341217041},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6049777269363403},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5828543901443481},{"id":"https://openalex.org/keywords/thematic-map","display_name":"Thematic map","score":0.5257730484008789},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5086208581924438},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4944167137145996},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4903731346130371},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.482570081949234},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.448516845703125},{"id":"https://openalex.org/keywords/remote-sensing-application","display_name":"Remote sensing application","score":0.4125773012638092},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3569541573524475},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22562497854232788},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.10865926742553711}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8807091116905212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7599695324897766},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6145661473274231},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6086733341217041},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6049777269363403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5828543901443481},{"id":"https://openalex.org/C93692415","wikidata":"https://www.wikidata.org/wiki/Q1502030","display_name":"Thematic map","level":2,"score":0.5257730484008789},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5086208581924438},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4944167137145996},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4903731346130371},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.482570081949234},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.448516845703125},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.4125773012638092},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3569541573524475},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22562497854232788},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.10865926742553711},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstars.2013.2251969","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2013.2251969","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W41004946","https://openalex.org/W1967709368","https://openalex.org/W1975580656","https://openalex.org/W2001298023","https://openalex.org/W2011737760","https://openalex.org/W2016648380","https://openalex.org/W2022470997","https://openalex.org/W2029064186","https://openalex.org/W2043665634","https://openalex.org/W2053956845","https://openalex.org/W2054804336","https://openalex.org/W2086762254","https://openalex.org/W2098057602","https://openalex.org/W2098622092","https://openalex.org/W2103699041","https://openalex.org/W2104269704","https://openalex.org/W2114819256","https://openalex.org/W2127597507","https://openalex.org/W2129066856","https://openalex.org/W2131697388","https://openalex.org/W2131864940","https://openalex.org/W2134594501","https://openalex.org/W2135009772","https://openalex.org/W2136251662","https://openalex.org/W2137641062","https://openalex.org/W2144966944","https://openalex.org/W2148791530","https://openalex.org/W2153534417","https://openalex.org/W2153635508","https://openalex.org/W2154231986","https://openalex.org/W2158275940","https://openalex.org/W2160199096","https://openalex.org/W2160662337","https://openalex.org/W2164330327","https://openalex.org/W2164741953","https://openalex.org/W2165796970","https://openalex.org/W2169201488","https://openalex.org/W2487087946","https://openalex.org/W2506684654","https://openalex.org/W2900032653","https://openalex.org/W3023540311","https://openalex.org/W3120740533","https://openalex.org/W4212863985","https://openalex.org/W4213009331","https://openalex.org/W4232222670","https://openalex.org/W4320339642","https://openalex.org/W6601609982"],"related_works":["https://openalex.org/W2351870625","https://openalex.org/W2411184991","https://openalex.org/W2341518107","https://openalex.org/W2349598717","https://openalex.org/W2385371209","https://openalex.org/W2496529405","https://openalex.org/W4234949831","https://openalex.org/W4327563507","https://openalex.org/W4313005088","https://openalex.org/W2165780522"],"abstract_inverted_index":{"In":[0,91,178],"the":[1,15,34,78,143,182,185,210,236,241,244],"past":[2],"few":[3],"years,":[4],"Hyperspectral":[5],"image":[6,48],"analysis":[7],"has":[8],"been":[9],"used":[10,134,212],"for":[11,22,199,202],"many":[12],"purposes":[13],"in":[14,155,219],"field":[16],"of":[17,36,51,53,68,77,89,184,221,227,243],"remote":[18],"sensing":[19],"and":[20,33,83,116,119,127,175,206,216,239],"importantly":[21],"land":[23],"cover":[24,27],"classification.":[25],"Land":[26],"classification":[28,108,139],"is":[29,40,49,102,148],"a":[30,41,61,65,74,85,98,161],"challenging":[31],"task":[32],"production":[35],"accurate":[37,104],"thematic":[38,99],"maps":[39],"common":[42],"goal":[43],"among":[44],"researchers.":[45],"A":[46],"hyperspectral":[47],"composed":[50],"hundreds":[52],"spectral":[54,115],"channels,":[55],"where":[56],"each":[57],"channel":[58],"refers":[59],"to":[60,73,96,135,141,180,234],"specific":[62],"wavelength.":[63],"Such":[64],"large":[66],"amount":[67],"information":[69],"may":[70],"lead":[71],"us":[72],"deeper":[75],"investigation":[76],"materials":[79],"on":[80,114,150],"Earth's":[81],"surface,":[82],"thus,":[84],"more":[86,103],"precise":[87],"interpretation":[88],"them.":[90],"this":[92],"work,":[93],"we":[94],"aim":[95],"produce":[97,136],"map":[100],"that":[101],"by":[105],"combining":[106,146],"multiple":[107],"methods.":[109],"Three":[110],"feature":[111],"representations":[112],"based":[113,149],"spatial":[117],"data":[118],"two":[120,170],"learning":[121],"algorithms":[122],"(Support":[123],"Vector":[124],"Machines":[125],"(SVM)":[126],"Multilayer":[128],"Perceptron":[129],"Neural":[130],"Network":[131],"(MLP))":[132],"were":[133,166,193],"six":[137],"different":[138,190],"methods":[140],"perform":[142],"combination.":[144],"Our":[145],"approach":[147],"Weighted":[151],"Linear":[152],"Combination":[153],"(WLC),":[154],"which":[156],"weights":[157,238],"are":[158,207],"found":[159],"using":[160,189,224],"Genetic":[162],"Algorithm":[163],"(GA)-WLC-GA.":[164],"Experiments":[165],"carried":[167],"out":[168],"with":[169],"well-known":[171],"datasets:":[172],"Indian":[173],"Pines":[174],"Pavia":[176],"University.":[177],"order":[179],"evaluate":[181],"robustness":[183],"proposed":[186],"combiner,":[187],"experiments":[188],"training":[191,228],"sizes":[192],"conducted.":[194],"They":[195],"show":[196],"promising":[197],"results":[198],"both":[200],"datasets":[201],"our":[203,230],"WLC-GA":[204],"proposal":[205,231],"better":[208],"than":[209],"widely":[211],"Majority":[213],"Vote":[214],"(MV)":[215],"Average":[217],"rules":[218],"terms":[220],"accuracy.":[222],"By":[223],"only":[225],"10%":[226],"samples,":[229],"was":[232],"able":[233],"find":[235],"best":[237],"overcome":[240],"drawbacks":[242],"traditional":[245],"combination":[246],"rules.":[247]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}