{"id":"https://openalex.org/W2517189067","doi":"https://doi.org/10.1109/tgrs.2016.2594848","title":"Laplacian Regularized Collaborative Graph for Discriminant Analysis of Hyperspectral Imagery","display_name":"Laplacian Regularized Collaborative Graph for Discriminant Analysis of Hyperspectral Imagery","publication_year":2016,"publication_date":"2016-08-12","ids":{"openalex":"https://openalex.org/W2517189067","doi":"https://doi.org/10.1109/tgrs.2016.2594848","mag":"2517189067"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2016.2594848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2016.2594848","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/A5100317994","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-7015-7335"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Li","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033017179","display_name":"Qian Du","orcid":"https://orcid.org/0000-0001-8354-7500"},"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":"Qian Du","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100317994"],"corresponding_institution_ids":["https://openalex.org/I75390827"],"apc_list":null,"apc_paid":null,"fwci":8.3967,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.97858414,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"54","issue":"12","first_page":"7066","last_page":"7076"},"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9830999970436096,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.846612274646759},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.522636890411377},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5150782465934753},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5030650496482849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5003528594970703},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4961915612220764},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.44157496094703674},{"id":"https://openalex.org/keywords/laplace-operator","display_name":"Laplace operator","score":0.420169472694397},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3958280086517334},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.3775281310081482},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3095925748348236},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10749316215515137}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.846612274646759},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.522636890411377},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5150782465934753},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5030650496482849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5003528594970703},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4961915612220764},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.44157496094703674},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.420169472694397},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3958280086517334},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3775281310081482},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3095925748348236},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10749316215515137},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2016.2594848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2016.2594848","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G1165116916","display_name":null,"funder_award_id":"BUCTRC201401","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5275275273","display_name":null,"funder_award_id":"BUCTRC201615","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G63620398","display_name":null,"funder_award_id":"61302164","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G755046186","display_name":null,"funder_award_id":"XK1521","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G768282616","display_name":null,"funder_award_id":"NSFC-61571033","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/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W625476304","https://openalex.org/W1517907761","https://openalex.org/W1591789348","https://openalex.org/W1897878572","https://openalex.org/W1904464160","https://openalex.org/W1968555645","https://openalex.org/W1992961908","https://openalex.org/W1997718749","https://openalex.org/W1997942468","https://openalex.org/W2000738214","https://openalex.org/W2004491663","https://openalex.org/W2012508386","https://openalex.org/W2026446464","https://openalex.org/W2037034832","https://openalex.org/W2053186076","https://openalex.org/W2054022051","https://openalex.org/W2058795991","https://openalex.org/W2064647952","https://openalex.org/W2069272294","https://openalex.org/W2069959554","https://openalex.org/W2072518892","https://openalex.org/W2075574309","https://openalex.org/W2077028485","https://openalex.org/W2078296814","https://openalex.org/W2089323474","https://openalex.org/W2090530010","https://openalex.org/W2090826137","https://openalex.org/W2093126287","https://openalex.org/W2098318489","https://openalex.org/W2103094532","https://openalex.org/W2103250033","https://openalex.org/W2108119513","https://openalex.org/W2114217318","https://openalex.org/W2118120419","https://openalex.org/W2127152713","https://openalex.org/W2132467081","https://openalex.org/W2142848040","https://openalex.org/W2145649962","https://openalex.org/W2151288205","https://openalex.org/W2151599207","https://openalex.org/W2152057649","https://openalex.org/W2154872931","https://openalex.org/W2155985040","https://openalex.org/W2158703175","https://openalex.org/W2164071167","https://openalex.org/W2165573608","https://openalex.org/W2183457690","https://openalex.org/W2314433345","https://openalex.org/W2319892480","https://openalex.org/W2331181944","https://openalex.org/W2345118402","https://openalex.org/W3148981562","https://openalex.org/W4285719527","https://openalex.org/W6675955514","https://openalex.org/W6677677282","https://openalex.org/W6682644385","https://openalex.org/W6686311551"],"related_works":["https://openalex.org/W2353567328","https://openalex.org/W2361282548","https://openalex.org/W3184937839","https://openalex.org/W2783789044","https://openalex.org/W1976359033","https://openalex.org/W3211035526","https://openalex.org/W2146076056","https://openalex.org/W2355238130","https://openalex.org/W2365193250","https://openalex.org/W1980318028"],"abstract_inverted_index":{"Collaborative":[0],"graph-based":[1,42],"discriminant":[2,43],"analysis":[3,44],"(CGDA)":[4],"has":[5],"been":[6],"recently":[7],"proposed":[8,113,158],"for":[9],"dimensionality":[10],"reduction":[11],"and":[12,65,132],"classification":[13,151],"of":[14,97,108,156],"hyperspectral":[15,150],"imagery,":[16],"offering":[17],"superior":[18],"performance.":[19,143],"In":[20],"CGDA,":[21],"a":[22,47,85,94],"graph":[23,48,96,110],"is":[24,49,91,100],"constructed":[25],"by":[26,51],"\u2113":[27,52],"<sub":[28,53],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[29,54],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sub>":[30],"-":[31,56],"norm":[32,57],"minimization-based":[33],"representation":[34,120],"using":[35],"available":[36],"labeled":[37],"samples.":[38],"Different":[39],"from":[40,61],"sparse":[41],"(SGDA)":[45],"where":[46,93],"built":[50],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[55],"minimization,":[58],"CGDA":[59,69,81,88,131],"benefits":[60],"within-class":[62],"sample":[63],"collaboration":[64],"computational":[66],"efficiency.":[67],"However,":[68],"does":[70],"not":[71,115],"consider":[72],"data":[73,98],"manifold":[74,99],"structure":[75],"reflecting":[76],"geometric":[77,127],"information.":[78,128],"To":[79],"improve":[80,141],"in":[82],"this":[83],"regard,":[84],"Laplacian":[86,95],"regularized":[87],"(LapCGDA)":[89],"framework":[90],"proposed,":[92],"incorporated":[101],"into":[102,136],"the":[103,109,112,125,142,154,157],"CGDA.":[104],"By":[105],"taking":[106],"advantage":[107],"regularizer,":[111],"method":[114],"only":[116],"can":[117,123],"offer":[118],"collaborative":[119],"but":[121],"also":[122],"exploit":[124],"intrinsic":[126],"Moreover,":[129],"both":[130],"LapCGDA":[133],"are":[134],"extended":[135],"kernel":[137],"versions":[138],"to":[139],"further":[140],"Experimental":[144],"results":[145],"on":[146],"several":[147],"different":[148],"multiple-class":[149],"tasks":[152],"demonstrate":[153],"effectiveness":[155],"LapCGDA.":[159]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
