{"id":"https://openalex.org/W4210576732","doi":"https://doi.org/10.1109/tgrs.2022.3144192","title":"Spectral-Spatial Deep Support Vector Data Description for Hyperspectral Anomaly Detection","display_name":"Spectral-Spatial Deep Support Vector Data Description for Hyperspectral Anomaly Detection","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4210576732","doi":"https://doi.org/10.1109/tgrs.2022.3144192"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3144192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3144192","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/A5101602255","display_name":"Kun Li","orcid":"https://orcid.org/0000-0002-0012-7322"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Li","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0012-7322","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062731814","display_name":"Qiang Ling","orcid":"https://orcid.org/0000-0003-4937-5420"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Ling","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-4937-5420","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029830288","display_name":"Yao Qin","orcid":"https://orcid.org/0000-0002-3777-6334"},"institutions":[{"id":"https://openalex.org/I4210151975","display_name":"Northwest Institute of Nuclear Technology","ror":"https://ror.org/04svrh266","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210151975"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Qin","raw_affiliation_strings":["Northwest Institute of Nuclear Technology, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-3777-6334","affiliations":[{"raw_affiliation_string":"Northwest Institute of Nuclear Technology, Xi’an, China","institution_ids":["https://openalex.org/I4210151975"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052232868","display_name":"Yingqian Wang","orcid":"https://orcid.org/0000-0002-9081-6227"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingqian Wang","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-9081-6227","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044359278","display_name":"Yaoming Cai","orcid":"https://orcid.org/0000-0002-2609-3036"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["CN","DE"],"is_corresponding":false,"raw_author_name":"Yaoming Cai","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China","Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-2609-3036","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany","institution_ids":["https://openalex.org/I4210148560","https://openalex.org/I2801798921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068849800","display_name":"Zaiping Lin","orcid":"https://orcid.org/0000-0002-1463-5838"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zaiping Lin","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032382317","display_name":"Wei An","orcid":"https://orcid.org/0000-0001-8319-2105"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei An","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3906,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.89861289,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"16"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9807000160217285,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9653000235557556,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7766671180725098},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7316568493843079},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7154608964920044},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7042793035507202},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.640408992767334},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5830106735229492},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5300742387771606},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44809064269065857},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42503949999809265},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4108723998069763}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7766671180725098},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7316568493843079},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7154608964920044},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7042793035507202},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.640408992767334},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5830106735229492},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5300742387771606},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44809064269065857},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42503949999809265},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4108723998069763},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3144192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3144192","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":[],"awards":[{"id":"https://openalex.org/G1302225335","display_name":null,"funder_award_id":"42101344","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2580802114","display_name":null,"funder_award_id":"62002372","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":67,"referenced_works":["https://openalex.org/W1990953362","https://openalex.org/W1991190032","https://openalex.org/W1997201895","https://openalex.org/W2004491663","https://openalex.org/W2017014096","https://openalex.org/W2024288510","https://openalex.org/W2047519171","https://openalex.org/W2047870694","https://openalex.org/W2067191022","https://openalex.org/W2067782748","https://openalex.org/W2067897118","https://openalex.org/W2118359036","https://openalex.org/W2124267685","https://openalex.org/W2124463804","https://openalex.org/W2145962650","https://openalex.org/W2158340226","https://openalex.org/W2163129097","https://openalex.org/W2165447611","https://openalex.org/W2288752886","https://openalex.org/W2295576075","https://openalex.org/W2343117455","https://openalex.org/W2500751094","https://openalex.org/W2590856740","https://openalex.org/W2603834682","https://openalex.org/W2740976805","https://openalex.org/W2750586932","https://openalex.org/W2752782242","https://openalex.org/W2796629918","https://openalex.org/W2800662010","https://openalex.org/W2807662216","https://openalex.org/W2892816441","https://openalex.org/W2893965284","https://openalex.org/W2898121906","https://openalex.org/W2900199428","https://openalex.org/W2937638900","https://openalex.org/W2959891261","https://openalex.org/W2964469941","https://openalex.org/W2964493519","https://openalex.org/W2972480129","https://openalex.org/W2972614519","https://openalex.org/W2975506318","https://openalex.org/W2983563481","https://openalex.org/W3003955104","https://openalex.org/W3005109735","https://openalex.org/W3008839601","https://openalex.org/W3015560401","https://openalex.org/W3021998006","https://openalex.org/W3043982729","https://openalex.org/W3080792885","https://openalex.org/W3087931076","https://openalex.org/W3105005050","https://openalex.org/W3122451732","https://openalex.org/W3123098349","https://openalex.org/W3124606680","https://openalex.org/W3124851637","https://openalex.org/W3126418353","https://openalex.org/W3137199127","https://openalex.org/W3158390871","https://openalex.org/W3176520651","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6640963894","https://openalex.org/W6675401909","https://openalex.org/W6681016373","https://openalex.org/W6682889407","https://openalex.org/W6739901393","https://openalex.org/W6780248173"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3017266184","https://openalex.org/W2918377632","https://openalex.org/W3202913553","https://openalex.org/W3194885736","https://openalex.org/W3046391934","https://openalex.org/W4363671829","https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961"],"abstract_inverted_index":{"Hyperspectral":[0],"anomaly":[1,52,62,125],"detection":[2,21,53,126,221],"(HAD)":[3],"aims":[4],"to":[5,16,30,51,55,101,146,161,182,214],"distinguish":[6],"anomalies":[7],"from":[8],"background-by-background":[9],"modeling.":[10],"Deep":[11],"learning":[12,60,123],"has":[13],"been":[14],"applied":[15],"HAD":[17,217],"and":[18,61,124,151,164,190],"achieves":[19],"promising":[20],"results.":[22],"However,":[23],"there":[24,134],"exist":[25],"several":[26,215],"issues":[27],"that":[28],"need":[29],"be":[31],"addressed:":[32],"1)":[33],"unrealistic":[34],"Gaussian":[35,138],"assumption":[36,139],"on":[37,140,202],"the":[38,56,103,141,147,193,207,210,220],"latent":[39],"representations":[40],"may":[41],"limit":[42],"its":[43],"application;":[44],"2)":[45],"deep":[46,88,104,171],"features":[47,105,166],"are":[48,112,127],"not":[49],"well-suited":[50],"due":[54,145],"separation":[57],"between":[58],"feature":[59,122,156],"detection;":[63],"3)":[64],"lack":[65],"of":[66,69,106,149,209],"adequate":[67],"exploitation":[68],"spectral-spatial":[70],"features;":[71],"4)":[72],"negative":[73,194],"effect":[74,195],"caused":[75,196],"by":[76,114,168,197],"spectral":[77,150,163],"band":[78,177],"redundancy.":[79],"In":[80,119],"this":[81,120],"article,":[82],"we":[83],"propose":[84],"an":[85],"end-to-end":[86],"trainable":[87],"one-class":[89],"classification":[90],"network":[91],"for":[92,187],"HAD.":[93],"Specifically,":[94],"a":[95,115,130,154,169,176],"minimal":[96],"enclosing":[97],"hypersphere":[98],"is":[99,135,159,180],"trained":[100],"involve":[102],"background":[107,110,142],"samples.":[108],"These":[109],"samples":[111],"selected":[113],"density":[116],"clustering-based":[117],"method.":[118],"way,":[121],"incorporated":[128],"into":[129],"unified":[131],"framework.":[132],"Meanwhile,":[133],"no":[136],"explicit":[137],"features.":[143],"Moreover,":[144],"complementarity":[148],"spatial":[152,165],"features,":[153],"novel":[155],"fusion":[157],"strategy":[158],"proposed":[160,211],"fuse":[162],"extracted":[167],"two-stream":[170],"convolutional":[172],"autoencoder":[173],"network.":[174],"Finally,":[175],"attention":[178],"module":[179],"used":[181],"automatically":[183],"learn":[184],"small":[185],"weights":[186],"redundant":[188,198],"bands":[189],"thus":[191],"reduce":[192],"bands.":[199],"Experimental":[200],"results":[201],"five":[203],"public":[204],"datasets":[205],"demonstrate":[206],"superiority":[208],"method":[212],"compared":[213],"state-of-the-art":[216],"methods":[218],"in":[219],"performance.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}