{"id":"https://openalex.org/W4390187403","doi":"https://doi.org/10.1109/tgrs.2023.3347270","title":"Self-Supervised Hyperspectral Anomaly Detection Based on Finite Spatialwise Attention","display_name":"Self-Supervised Hyperspectral Anomaly Detection Based on Finite Spatialwise Attention","publication_year":2023,"publication_date":"2023-12-25","ids":{"openalex":"https://openalex.org/W4390187403","doi":"https://doi.org/10.1109/tgrs.2023.3347270"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3347270","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3347270","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/A5100424154","display_name":"Zhipeng Wang","orcid":"https://orcid.org/0000-0002-1145-234X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]},{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]},{"id":"https://openalex.org/I4392738113","display_name":"China Electric Power Research Institute","ror":"https://ror.org/05ehpzy81","country_code":null,"type":"facility","lineage":["https://openalex.org/I17442442","https://openalex.org/I4392738113"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Wang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China","China Electric Power Research Institute, State Grid Corporation of China, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1145-234X","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"China Electric Power Research Institute, State Grid Corporation of China, Beijing, China","institution_ids":["https://openalex.org/I17442442","https://openalex.org/I4392738113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074786060","display_name":"Dan Ma","orcid":"https://orcid.org/0009-0002-2262-9603"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Ma","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0002-2262-9603","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030883042","display_name":"Guanghui Yue","orcid":"https://orcid.org/0000-0002-6761-8767"},"institutions":[{"id":"https://openalex.org/I4210145292","display_name":"Shenzhen University Health Science Center","ror":"https://ror.org/04yjbr930","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210145292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanghui Yue","raw_affiliation_strings":["Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-6761-8767","affiliations":[{"raw_affiliation_string":"Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I4210145292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031123060","display_name":"Beichen Li","orcid":"https://orcid.org/0000-0002-3621-0478"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Beichen Li","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-3621-0478","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091558139","display_name":"Runmin Cong","orcid":"https://orcid.org/0000-0003-0972-4008"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runmin Cong","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0003-0972-4008","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031071245","display_name":"Zhiqiang Wu","orcid":"https://orcid.org/0000-0001-9055-5680"},"institutions":[{"id":"https://openalex.org/I140786321","display_name":"Tibet University","ror":"https://ror.org/05petvd47","country_code":"CN","type":"education","lineage":["https://openalex.org/I140786321"]},{"id":"https://openalex.org/I19648265","display_name":"Wright State University","ror":"https://ror.org/04qk6pt94","country_code":"US","type":"education","lineage":["https://openalex.org/I19648265"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Zhiqiang Wu","raw_affiliation_strings":["Department of Electrical Engineering, Tibet University, Lhasa, China","Department of Electrical Engineering, Wright State University, Dayton, OH, USA"],"raw_orcid":"https://orcid.org/0000-0001-9055-5680","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Tibet University, Lhasa, China","institution_ids":["https://openalex.org/I140786321"]},{"raw_affiliation_string":"Department of Electrical Engineering, Wright State University, Dayton, OH, USA","institution_ids":["https://openalex.org/I19648265"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0712,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.7816013,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9674000144004822,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9136999845504761,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8703604936599731},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7810945510864258},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7264758348464966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6642011404037476},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6197699904441833},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5839004516601562},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.43668490648269653},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4127141535282135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3655329942703247},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32928580045700073},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11110511422157288}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8703604936599731},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7810945510864258},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7264758348464966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6642011404037476},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6197699904441833},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5839004516601562},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.43668490648269653},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4127141535282135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3655329942703247},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32928580045700073},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11110511422157288},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3347270","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3347270","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/G2481038826","display_name":null,"funder_award_id":"62101378","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3862919903","display_name":null,"funder_award_id":"U20A20162","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5971526899","display_name":null,"funder_award_id":"62171318","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6370623351","display_name":null,"funder_award_id":"62371305","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1991190032","https://openalex.org/W2004491663","https://openalex.org/W2024288510","https://openalex.org/W2040078680","https://openalex.org/W2047870694","https://openalex.org/W2048625826","https://openalex.org/W2067897118","https://openalex.org/W2076603174","https://openalex.org/W2104960492","https://openalex.org/W2124463804","https://openalex.org/W2140340527","https://openalex.org/W2163129097","https://openalex.org/W2183325870","https://openalex.org/W2295576075","https://openalex.org/W2303627748","https://openalex.org/W2590856740","https://openalex.org/W2592141703","https://openalex.org/W2607289818","https://openalex.org/W2796629918","https://openalex.org/W2799954862","https://openalex.org/W2802866486","https://openalex.org/W2884073548","https://openalex.org/W2886820760","https://openalex.org/W2917647353","https://openalex.org/W2959891261","https://openalex.org/W2975506318","https://openalex.org/W2979897847","https://openalex.org/W3003955104","https://openalex.org/W3007076381","https://openalex.org/W3080792885","https://openalex.org/W3114010851","https://openalex.org/W3122722892","https://openalex.org/W3123098349","https://openalex.org/W3131922516","https://openalex.org/W3137199127","https://openalex.org/W3138516171","https://openalex.org/W3159648608","https://openalex.org/W3166166117","https://openalex.org/W3171125843","https://openalex.org/W3186256209","https://openalex.org/W3214821343","https://openalex.org/W3217610095","https://openalex.org/W4212800897","https://openalex.org/W4223616928","https://openalex.org/W4224294196","https://openalex.org/W4225582357","https://openalex.org/W4285059972","https://openalex.org/W4285181756","https://openalex.org/W4285258250","https://openalex.org/W4285303509","https://openalex.org/W4292691763","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6778883912","https://openalex.org/W6803550384","https://openalex.org/W7055499513"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4300558037","https://openalex.org/W4377864969","https://openalex.org/W3030345572"],"abstract_inverted_index":{"Hyperspectral":[0,82,101],"anomaly":[1,45],"detection":[2,46],"(HAD)":[3],"is":[4,97],"of":[5,19,94,112,129,137,155,190],"great":[6],"value":[7],"in":[8,64,159],"both":[9],"practical":[10,65],"and":[11,41,56,133,169,188],"theoretical":[12],"terms.":[13],"However,":[14],"due":[15],"to":[16,32,43,116],"the":[17,69,80,88,98,108,127,135,152,156,164,186,191],"lack":[18],"available":[20],"semantic":[21,39,131],"labels,":[22],"previous":[23,51],"works":[24],"mainly":[25],"relied":[26],"on":[27,87,181],"unsupervised":[28],"or":[29],"semi-supervised":[30],"methods":[31,52],"construct":[33],"learning":[34],"models,":[35],"which":[36,60,125],"inevitably":[37],"lacked":[38],"guidance":[40],"led":[42],"limited":[44],"(AD)":[47],"effectiveness.":[48],"Besides,":[49],"few":[50],"jointly":[53],"mine":[54],"spectral":[55,110],"spatial":[57],"global":[58],"dependencies,":[59],"limits":[61],"their":[62],"effectiveness":[63,187],"scenarios.":[66],"To":[67],"address":[68],"above":[70],"problems,":[71],"we":[72,142],"design":[73],"a":[74,121,144,160],"novel":[75],"self-supervised":[76],"HAD":[77],"method,":[78],"named":[79],"Self-Supervised":[81,100],"Anomaly":[83,102],"Detection":[84,103],"method":[85,96],"based":[86],"Finite":[89,145],"Spatial-wise":[90,146],"Attention.":[91],"The":[92,149],"core":[93],"proposed":[95,192],"designed":[99],"transFormer":[104],"(SSHADFormer).":[105],"It":[106],"explores":[107],"specific":[109],"attributes":[111],"hyperspectral":[113],"images":[114],"(HSIs)":[115],"reconstruct":[117],"background":[118,157,168],"HSI":[119],"from":[120],"given":[122],"RGB":[123],"image,":[124],"solves":[126],"difficulty":[128],"acquiring":[130],"information":[132],"enhances":[134],"agility":[136,189],"AD":[138],"models.":[139],"In":[140],"addition,":[141],"propose":[143],"Attention":[147],"mechanism.":[148],"mechanism":[150],"mines":[151],"cluster":[153],"structure":[154],"spectrum":[158],"data-driven":[161],"manner,":[162],"enhancing":[163],"discriminative":[165],"ability":[166],"between":[167],"anomalous":[170,174],"targets":[171,175],"while":[172],"avoiding":[173],"interference":[176],"during":[177],"training.":[178],"Extensive":[179],"experiments":[180],"six":[182],"public":[183],"datasets":[184],"demonstrate":[185],"method.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
