{"id":"https://openalex.org/W2148215686","doi":"https://doi.org/10.1109/whispers.2009.5288983","title":"Sensitivity of hyperspectral classification algorithms to training sample size","display_name":"Sensitivity of hyperspectral classification algorithms to training sample size","publication_year":2009,"publication_date":"2009-08-01","ids":{"openalex":"https://openalex.org/W2148215686","doi":"https://doi.org/10.1109/whispers.2009.5288983","mag":"2148215686"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2009.5288983","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2009.5288983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5091152839","display_name":"M.A. Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M.A. Lee","raw_affiliation_strings":["Electrical and Computer Engineering Department, Mississippi State University, Mississippi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Mississippi State University, Mississippi","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037823063","display_name":"Saurabh Prasad","orcid":"https://orcid.org/0000-0003-3729-9360"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S. Prasad","raw_affiliation_strings":["Geosystems Research Institute, Mississippi State University, Mississippi, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Geosystems Research Institute, Mississippi State University, Mississippi, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103103246","display_name":"L.M. Bruce","orcid":"https://orcid.org/0000-0002-9380-1143"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"L.M. Bruce","raw_affiliation_strings":["Electrical and Computer Engineering Department, Mississippi State University, Mississippi, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Mississippi State University, Mississippi, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049840877","display_name":"T.R. West","orcid":null},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T.R. West","raw_affiliation_strings":["Electrical and Computer Engineering Department, Mississippi State University, Mississippi, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Mississippi State University, Mississippi, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111945151","display_name":"D.A. Reynolds","orcid":null},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. Reynolds","raw_affiliation_strings":["Plant and Soil Science Department, Mississippi State University, Mississippi, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Plant and Soil Science Department, Mississippi State University, Mississippi, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109785944","display_name":"T. Irby","orcid":null},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T. Irby","raw_affiliation_strings":["Plant and Soil Science Department, Mississippi State University, Mississippi, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Plant and Soil Science Department, Mississippi State University, Mississippi, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050069426","display_name":"Hemanth Kalluri","orcid":null},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H. Kalluri","raw_affiliation_strings":["Electrical and Computer Engineering Department, Mississippi State University, Mississippi, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Mississippi State University, Mississippi, USA","institution_ids":["https://openalex.org/I99041443"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99041443"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9879000186920166,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9855999946594238,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.846586287021637},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6261268258094788},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5450466275215149},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46619290113449097},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4587095379829407},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4565512537956238},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44269484281539917},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.4172283709049225},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.41049572825431824},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.3734017610549927},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.2768862247467041},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15279620885849}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.846586287021637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6261268258094788},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5450466275215149},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46619290113449097},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4587095379829407},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4565512537956238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44269484281539917},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.4172283709049225},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.41049572825431824},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3734017610549927},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.2768862247467041},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15279620885849},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2009.5288983","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2009.5288983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W608571397","https://openalex.org/W2112556443","https://openalex.org/W2132532785","https://openalex.org/W2144151128","https://openalex.org/W2799061466","https://openalex.org/W4205687621","https://openalex.org/W4243464025"],"related_works":["https://openalex.org/W2132083814","https://openalex.org/W2981877337","https://openalex.org/W3203938600","https://openalex.org/W2169074127","https://openalex.org/W4286910063","https://openalex.org/W83146503","https://openalex.org/W2163707935","https://openalex.org/W202723009","https://openalex.org/W2145955964","https://openalex.org/W2188612292"],"abstract_inverted_index":{"Algorithms":[0],"that":[1,121],"exploit":[2],"hyperspectral":[3,99,109],"imagery":[4],"often":[5],"encounter":[6],"problems":[7],"related":[8],"to":[9,30,85,139,197,224,241,254],"the":[10,14,18,32,49,54,57,61,70,88,95,117,123,126,136,178,221,238],"high":[11,235],"dimensionality":[12],"of":[13,20,72,90,116,149,164,172,180,190,201,216,252],"data,":[15],"particularly":[16],"when":[17,159],"amount":[19,89],"training":[21,94,141,165,173,187,213,242],"data":[22,91,100,166,188,214,243],"is":[23,39,161,175],"limited.":[24],"Recently,":[25],"two":[26],"algorithms":[27,130,138],"were":[28],"proposed":[29],"alleviate":[31],"small":[33],"sample":[34],"size":[35],"problem":[36],"-":[37,167],"one":[38],"based":[40,76],"on":[41],"employing":[42],"a":[43],"Multi-Classifier":[44],"Decision":[45],"Fusion":[46],"(MCDF)":[47],"in":[48,60,87,101,146,205,234],"raw":[50],"reflectance":[51],"domain,":[52],"and":[53,83,128,192,210,218,228],"other":[55],"employed":[56,92],"MCDF":[58,82,127,203],"framework":[59],"Discrete":[62],"Wavelet":[63],"Transform":[64],"domain":[65],"(DWT-MCDF).":[66],"This":[67],"paper":[68],"investigates":[69],"sensitivity":[71,240],"conventional":[73,137],"single":[74],"classifier":[75],"classification":[77,96],"approaches,":[78],"as":[79,81],"well":[80],"DWT-MCDF":[84,129,232],"variations":[86],"for":[93,122,186,199,212,226,230,250],"system.":[97],"The":[98,114],"this":[102],"experiment":[103],"was":[104],"obtained":[105],"using":[106],"an":[107,162],"airborne":[108],"imager":[110],"used":[111],"by":[112],"SpecTIRtrade.":[113],"results":[115,145,204,233],"experimental":[118],"analysis":[119],"show":[120],"given":[124],"application,":[125],"are":[131,154],"significantly":[132],"less":[133],"sensitive":[134],"than":[135],"limited":[140],"data.":[142],"PCA":[143],"consistently":[144],"overall":[147],"accuracies":[148,153,206,222,236,246],"about":[150,157,168],"35%.":[151],"LDA":[152],"very":[155],"high,":[156],"75%,":[158],"there":[160],"abundance":[163,215],"10X":[169],"(i.e.":[170],"number":[171,179],"samples":[174],"10":[176],"times":[177],"spectral":[181],"bands);":[182],"remains":[183],"above":[184],"60%":[185],"abundances":[189,200,251],"2X":[191,227],"higher;":[193],"but":[194,220],"dramatically":[195],"decreases":[196],"~20%":[198],"1X.":[202,231],"ranging":[207],"between":[208,248],"65%":[209],"75%":[211],"3X":[217],"higher,":[219],"drop":[223],"~60%":[225],"~55%":[229],"with":[237],"least":[239],"abundance.":[244],"Its":[245],"range":[247],"~60-65%":[249],"1X":[253],"10X.":[255]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}