{"id":"https://openalex.org/W2595650414","doi":"https://doi.org/10.1109/lgrs.2017.2671852","title":"Kernel Fused Representation-Based Classifier for Hyperspectral Imagery","display_name":"Kernel Fused Representation-Based Classifier for Hyperspectral Imagery","publication_year":2017,"publication_date":"2017-03-15","ids":{"openalex":"https://openalex.org/W2595650414","doi":"https://doi.org/10.1109/lgrs.2017.2671852","mag":"2595650414"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2017.2671852","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2017.2671852","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5046938347","display_name":"Le Gan","orcid":"https://orcid.org/0000-0002-8260-6932"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]},{"id":"https://openalex.org/I4210157323","display_name":"South China Institute of Collaborative Innovation","ror":"https://ror.org/04jnpk588","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210157323","https://openalex.org/I90610280"]},{"id":"https://openalex.org/I4210141849","display_name":"National Administration of Surveying, Mapping and Geoinformation of China","ror":"https://ror.org/04z3map19","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210141849"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Le Gan","raw_affiliation_strings":["Collaborative Innovation Center of South China Sea Studies, Nanjing, China","Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center of South China Sea Studies, Nanjing, China","institution_ids":["https://openalex.org/I4210157323"]},{"raw_affiliation_string":"Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I4210141849","https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690406","display_name":"Peijun Du","orcid":"https://orcid.org/0000-0002-2488-2656"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]},{"id":"https://openalex.org/I4210157323","display_name":"South China Institute of Collaborative Innovation","ror":"https://ror.org/04jnpk588","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210157323","https://openalex.org/I90610280"]},{"id":"https://openalex.org/I4210141849","display_name":"National Administration of Surveying, Mapping and Geoinformation of China","ror":"https://ror.org/04z3map19","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210141849"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peijun Du","raw_affiliation_strings":["Collaborative Innovation Center of South China Sea Studies, Nanjing, China","Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center of South China Sea Studies, Nanjing, China","institution_ids":["https://openalex.org/I4210157323"]},{"raw_affiliation_string":"Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I4210141849","https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000395252","display_name":"Junshi Xia","orcid":"https://orcid.org/0000-0002-5586-6536"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Junshi Xia","raw_affiliation_strings":["Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035533302","display_name":"Yaping Meng","orcid":"https://orcid.org/0000-0002-5918-7100"},"institutions":[{"id":"https://openalex.org/I4210157323","display_name":"South China Institute of Collaborative Innovation","ror":"https://ror.org/04jnpk588","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210157323","https://openalex.org/I90610280"]},{"id":"https://openalex.org/I4210141849","display_name":"National Administration of Surveying, Mapping and Geoinformation of China","ror":"https://ror.org/04z3map19","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210141849"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaping Meng","raw_affiliation_strings":["Collaborative Innovation Center of South China Sea Studies, Nanjing, China","Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center of South China Sea Studies, Nanjing, China","institution_ids":["https://openalex.org/I4210157323"]},{"raw_affiliation_string":"Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I4210141849","https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5046938347"],"corresponding_institution_ids":["https://openalex.org/I4210141849","https://openalex.org/I4210157323","https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":4.2371,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.94712257,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"14","issue":"5","first_page":"684","last_page":"688"},"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":0.9922000169754028,"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/T10057","display_name":"Face and Expression Recognition","score":0.9865000247955322,"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":0.8490967750549316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6975974440574646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6928206086158752},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6841552257537842},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5997674465179443},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5223159193992615},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.34736090898513794},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3221932649612427},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1572677493095398},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11398166418075562}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8490967750549316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6975974440574646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6928206086158752},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6841552257537842},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5997674465179443},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5223159193992615},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.34736090898513794},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3221932649612427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1572677493095398},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11398166418075562},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2017.2671852","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2017.2671852","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1069859310","display_name":null,"funder_award_id":"41471275","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1672851775","https://openalex.org/W1799946925","https://openalex.org/W1808256548","https://openalex.org/W1964749215","https://openalex.org/W1973521730","https://openalex.org/W1979158807","https://openalex.org/W1997565609","https://openalex.org/W2056302425","https://openalex.org/W2100975942","https://openalex.org/W2104269704","https://openalex.org/W2113464037","https://openalex.org/W2129812935","https://openalex.org/W2132467081","https://openalex.org/W2142848040","https://openalex.org/W2144348684","https://openalex.org/W2151599207","https://openalex.org/W2164437025","https://openalex.org/W2316226477","https://openalex.org/W2335607901","https://openalex.org/W2395443950","https://openalex.org/W2762869430","https://openalex.org/W3099014258","https://openalex.org/W6637220020","https://openalex.org/W6638482740"],"related_works":["https://openalex.org/W2783789044","https://openalex.org/W3211035526","https://openalex.org/W1869808405","https://openalex.org/W2028628118","https://openalex.org/W2031007444","https://openalex.org/W2775464024","https://openalex.org/W2972973180","https://openalex.org/W1491778359","https://openalex.org/W4293272463","https://openalex.org/W4291701050"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"we":[3,32],"propose":[4],"a":[5,25,56,79],"kernel":[6,27,36,39,43,58,72,93,121],"fused":[7,122],"representation-based":[8,28,130],"classifier":[9],"(KFRC)":[10],"for":[11,110],"hyperspectral":[12],"images":[13],"(HSIs),":[14],"which":[15,46],"combines":[16],"sparse":[17],"representation":[18,22,49,73],"(SR)":[19],"and":[20,42,83],"collaborative":[21],"(CR)":[23],"into":[24,55],"unified":[26],"classification":[29],"framework.":[30],"First,":[31],"present":[33],"two":[34,71,116],"individual":[35],"methods,":[37],"i.e.,":[38],"SR":[40],"(KSR)":[41],"CR":[44],"(KCR),":[45],"kernelize":[47],"the":[48,53,62,70,92,97,107,119,127],"methods":[50],"by":[51,106],"projecting":[52],"samples":[54,63],"high-dimensional":[57],"space":[59],"to":[60,77],"improve":[61],"separability":[64],"between":[65,81],"different":[66],"classes.":[67],"Once":[68],"obtaining":[69],"coefficients,":[74],"KFRC":[75],"attempts":[76],"achieve":[78],"balance":[80],"KSR":[82],"KCR":[84],"via":[85],"an":[86],"adjusting":[87],"parameter":[88],"$\\theta":[89],"$":[90],"in":[91],"residual":[94,109],"domain.":[95],"Subsequently,":[96],"class":[98],"label":[99],"of":[100],"each":[101,111],"test":[102],"sample":[103],"is":[104],"determined":[105],"minimum":[108],"class.":[112],"Experimental":[113],"results":[114],"on":[115],"HSIs":[117],"demonstrate":[118],"proposed":[120],"method":[123],"performs":[124],"better":[125],"than":[126],"other":[128],"state-of-the-art":[129],"classifiers.":[131]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
