{"id":"https://openalex.org/W4388838059","doi":"https://doi.org/10.1109/tgrs.2023.3334562","title":"Background-Guided Deformable Convolutional Autoencoder for Hyperspectral Anomaly Detection","display_name":"Background-Guided Deformable Convolutional Autoencoder for Hyperspectral Anomaly Detection","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388838059","doi":"https://doi.org/10.1109/tgrs.2023.3334562"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3334562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3334562","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/A5032939140","display_name":"Zhaoyue Wu","orcid":"https://orcid.org/0000-0002-6797-2440"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Zhaoyue Wu","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046123228","display_name":"Mercedes E. Paoletti","orcid":"https://orcid.org/0000-0003-1030-3729"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Mercedes E. Paoletti","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019014062","display_name":"Hongjun Su","orcid":"https://orcid.org/0000-0002-8991-8568"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjun Su","raw_affiliation_strings":["College of Geography and Remote Sensing, Hohai University, Nanjing, China","School of Earth Sciences and Engineering, Hohai University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Geography and Remote Sensing, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]},{"raw_affiliation_string":"School of Earth Sciences and Engineering, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033046838","display_name":"Xuanwen Tao","orcid":"https://orcid.org/0000-0003-1093-0079"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Xuanwen Tao","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075007359","display_name":"Lirong Han","orcid":"https://orcid.org/0000-0002-8613-7037"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Lirong Han","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039673511","display_name":"Juan M. Haut","orcid":"https://orcid.org/0000-0001-6701-961X"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan M. Haut","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054292278","display_name":"Antonio Plaza","orcid":"https://orcid.org/0000-0002-9613-1659"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Plaza","raw_affiliation_strings":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, University of Extremadura, C&#x00E1;ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5032939140"],"corresponding_institution_ids":["https://openalex.org/I80606768"],"apc_list":null,"apc_paid":null,"fwci":3.4928,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.93563015,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"61","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/T13890","display_name":"Remote Sensing and Land Use","score":0.9905999898910522,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9544000029563904,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/autoencoder","display_name":"Autoencoder","score":0.876394510269165},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7843687534332275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6222540140151978},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6109259724617004},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5992559194564819},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.573458194732666},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.517924964427948},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5055711269378662},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5051279664039612},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49295997619628906},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.48765599727630615},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48532432317733765},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.46426108479499817},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3995821475982666},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20587903261184692}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.876394510269165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7843687534332275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6222540140151978},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6109259724617004},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5992559194564819},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.573458194732666},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.517924964427948},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5055711269378662},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5051279664039612},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49295997619628906},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.48765599727630615},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48532432317733765},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.46426108479499817},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3995821475982666},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20587903261184692},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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.2023.3334562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3334562","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":[{"score":0.6000000238418579,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1058977399","display_name":null,"funder_award_id":"PID2019-110315RB-I00","funder_id":"https://openalex.org/F4320322930","funder_display_name":"Ministerio de Ciencia e Innovaci\u00f3n"},{"id":"https://openalex.org/G2730839137","display_name":null,"funder_award_id":"202106710022","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G5054209810","display_name":null,"funder_award_id":"GR21040","funder_id":"https://openalex.org/F4320311049","funder_display_name":"Consejer\u00eda de Econom\u00eda y Hacienda"},{"id":"https://openalex.org/G5472889728","display_name":null,"funder_award_id":"42371327","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8830056459","display_name":null,"funder_award_id":"42122008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320311049","display_name":"Consejer\u00eda de Econom\u00eda y Hacienda","ror":"https://ror.org/0193wdc07"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320322930","display_name":"Ministerio de Ciencia e Innovaci\u00f3n","ror":"https://ror.org/034900433"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1971358070","https://openalex.org/W1981939910","https://openalex.org/W2004491663","https://openalex.org/W2011147915","https://openalex.org/W2047870694","https://openalex.org/W2124463804","https://openalex.org/W2131697388","https://openalex.org/W2163129097","https://openalex.org/W2288752886","https://openalex.org/W2295576075","https://openalex.org/W2424277038","https://openalex.org/W2592141703","https://openalex.org/W2740976805","https://openalex.org/W2898121906","https://openalex.org/W2911876518","https://openalex.org/W2963091558","https://openalex.org/W2966926453","https://openalex.org/W2972614519","https://openalex.org/W2983563481","https://openalex.org/W2987833009","https://openalex.org/W2988878652","https://openalex.org/W2991616716","https://openalex.org/W2998940023","https://openalex.org/W3003955104","https://openalex.org/W3005109735","https://openalex.org/W3010770313","https://openalex.org/W3015560401","https://openalex.org/W3025704205","https://openalex.org/W3087931076","https://openalex.org/W3111299748","https://openalex.org/W3112037842","https://openalex.org/W3137199127","https://openalex.org/W3153686193","https://openalex.org/W3157052017","https://openalex.org/W3158390871","https://openalex.org/W3164530652","https://openalex.org/W3177186825","https://openalex.org/W3186256209","https://openalex.org/W3199351457","https://openalex.org/W4210576732","https://openalex.org/W4210824752","https://openalex.org/W4212800897","https://openalex.org/W4282929851","https://openalex.org/W4285130035","https://openalex.org/W4285181756","https://openalex.org/W4285233009","https://openalex.org/W4289823735","https://openalex.org/W4292672241","https://openalex.org/W4296210064","https://openalex.org/W4312965086","https://openalex.org/W4319866034","https://openalex.org/W4319990014","https://openalex.org/W4321380750","https://openalex.org/W4321488108","https://openalex.org/W4327663519","https://openalex.org/W4360993974","https://openalex.org/W4366678167","https://openalex.org/W4367146981","https://openalex.org/W4367663470","https://openalex.org/W4367663491","https://openalex.org/W4368232741","https://openalex.org/W4376607587","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3017266184","https://openalex.org/W3194885736","https://openalex.org/W3046391934","https://openalex.org/W4363671829","https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4313561566"],"abstract_inverted_index":{"Autoencoder-based":[0],"hyperspectral":[1],"anomaly":[2],"detectors":[3,12],"have":[4],"received":[5],"significant":[6],"attention.":[7],"The":[8],"core":[9],"of":[10,39,73,153,172,190,204,207,239],"these":[11],"is":[13,106,127,143,175,186,195],"to":[14,111,118,129,135,145,156],"reconstruct":[15,41],"backgrounds":[16],"by":[17,26,216],"optimizing":[18],"autoencoders":[19],"so":[20],"that":[21,251],"anomalies":[22,155],"can":[23],"be":[24],"detected":[25],"reconstruction":[27,71],"residuals.":[28],"Nevertheless,":[29],"existing":[30],"methods":[31],"are":[32,214,260],"flawed":[33],"in":[34,49,56,256],"two":[35,183],"aspects:":[36],"1)":[37],"most":[38],"them":[40],"the":[42,46,64,69,74,77,102,113,151,162,169,178,188,191,202,208,211,217,226,236,240,252,257],"background":[43,98,165,218],"along":[44],"with":[45,89],"anomalies,":[47],"resulting":[48],"undesired":[50],"performance":[51,238],"for":[52],"large":[53],"target":[54],"detection":[55],"complex":[57,120],"backgrounds;":[58],"2)":[59],"they":[60],"only":[61],"focus":[62,157],"on":[63,158],"encoder":[65,209],"optimization":[66],"part,":[67],"ignoring":[68],"decoder":[70,212],"quality":[72],"background.":[75],"Given":[76],"above,":[78],"this":[79],"paper":[80],"proposes":[81],"a":[82,124,141,164,197,223],"background-guided":[83],"deformable":[84,104],"convolutional":[85],"autoencoder":[86],"(DCAE)":[87],"network":[88,180,227,258],"three":[90],"mutually":[91],"supportive":[92],"parts,":[93],"including":[94],"encoder,":[95,103],"decoder,":[96,163,192],"and":[97,193,210,229,246],"guidance":[99,166,219],"modules.":[100],"In":[101,161],"convolution":[105,110,126],"introduced":[107,128,255],"into":[108],"regular":[109],"build":[112,130],"adaptive":[114],"spatial":[115,121,138],"feature":[116,133],"extractor":[117,134],"fit":[119],"structures,":[122],"whilst":[123],"non-local":[125],"an":[131],"external":[132],"capture":[136],"global":[137],"relationships.":[139],"Further,":[140],"mask":[142],"designed":[144],"filter":[146],"potential":[147],"anomalous":[148],"information,":[149],"curbing":[150],"representation":[152],"high-frequency":[154],"widespread":[159],"backgrounds.":[160],"module":[167],"(considering":[168],"physical":[170],"meaning":[171],"linear":[173],"reconstruction)":[174],"built,":[176],"guiding":[177],"proposed":[179,241],"learning":[181,248],"via":[182],"strategies.":[184],"One":[185],"initializing":[187],"weight":[189],"another":[194],"adding":[196],"loss":[198],"term.":[199],"Notably,":[200],"both":[201],"number":[203],"output":[205],"channels":[206],"construction":[213],"determined":[215],"module,":[220],"which":[221,243],"creates":[222],"bridge":[224],"between":[225],"design":[228],"practical":[230],"situations.":[231],"A":[232],"profound":[233],"analysis":[234],"demonstrates":[235],"outstanding":[237],"method,":[242],"outperforms":[244],"traditional":[245],"deep":[247],"methods,":[249],"proving":[250],"novel":[253],"designs":[254],"architecture":[259],"extremely":[261],"effective.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":9}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
