{"id":"https://openalex.org/W4387164664","doi":"https://doi.org/10.1109/tgrs.2023.3320867","title":"S2G2HAD: A Graph-Guided Siamese Reconstruction Network for Hyperspectral Anomaly Detection","display_name":"S2G2HAD: A Graph-Guided Siamese Reconstruction Network for Hyperspectral Anomaly Detection","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387164664","doi":"https://doi.org/10.1109/tgrs.2023.3320867"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3320867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3320867","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/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":true,"raw_author_name":"Dan Ma","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"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/A5023247075","display_name":"Yonghong Hou","orcid":"https://orcid.org/0000-0002-1676-5505"},"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":"Yonghong Hou","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"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/A5100730802","display_name":"Minghao Chen","orcid":"https://orcid.org/0000-0002-2871-5812"},"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":"Minghao Chen","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"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/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"],"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/A5100424154","display_name":"Zhipeng Wang","orcid":"https://orcid.org/0000-0002-1145-234X"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]},{"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":["China Electric Power Research Institute (CEPRI), Beijing, China","China Electric Power Research Institute (CEPRI), Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Electric Power Research Institute (CEPRI), Beijing, China","institution_ids":["https://openalex.org/I153473198","https://openalex.org/I4392738113"]},{"raw_affiliation_string":"China Electric Power Research Institute (CEPRI), Beijing, Beijing, China","institution_ids":["https://openalex.org/I153473198","https://openalex.org/I4392738113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100703869","display_name":"Menglong Li","orcid":"https://orcid.org/0000-0002-2766-7329"},"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":"Menglong Li","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5074786060"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.9526,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78770116,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"21"},"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9627000093460083,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9358999729156494,"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":0.8166995048522949},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6745024919509888},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6569185853004456},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6140532493591309},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.604914128780365},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5862637758255005},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5371478199958801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5280095934867859},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5180482864379883},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4342021644115448},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42021244764328003},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4152246415615082},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16497015953063965}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8166995048522949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6745024919509888},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6569185853004456},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6140532493591309},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.604914128780365},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5862637758255005},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5371478199958801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5280095934867859},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5180482864379883},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4342021644115448},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42021244764328003},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4152246415615082},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16497015953063965},{"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.2023.3320867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3320867","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/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/G888847521","display_name":null,"funder_award_id":"61731003","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":65,"referenced_works":["https://openalex.org/W1484672383","https://openalex.org/W1665214252","https://openalex.org/W1991190032","https://openalex.org/W2004491663","https://openalex.org/W2024288510","https://openalex.org/W2047870694","https://openalex.org/W2048625826","https://openalex.org/W2104960492","https://openalex.org/W2135431554","https://openalex.org/W2171590421","https://openalex.org/W2303627748","https://openalex.org/W2497075055","https://openalex.org/W2764323333","https://openalex.org/W2783473861","https://openalex.org/W2800662010","https://openalex.org/W2808776742","https://openalex.org/W2884073548","https://openalex.org/W2898121906","https://openalex.org/W2967689968","https://openalex.org/W2972392244","https://openalex.org/W2975506318","https://openalex.org/W2979897847","https://openalex.org/W2997043451","https://openalex.org/W3003955104","https://openalex.org/W3007076381","https://openalex.org/W3008839601","https://openalex.org/W3014865789","https://openalex.org/W3080792885","https://openalex.org/W3123098349","https://openalex.org/W3124863755","https://openalex.org/W3126418353","https://openalex.org/W3134586917","https://openalex.org/W3157052017","https://openalex.org/W3163682380","https://openalex.org/W3164714368","https://openalex.org/W3183729446","https://openalex.org/W3186256209","https://openalex.org/W3196267160","https://openalex.org/W3205614732","https://openalex.org/W3208740751","https://openalex.org/W3211415248","https://openalex.org/W3212622989","https://openalex.org/W3214719104","https://openalex.org/W3217580681","https://openalex.org/W4200080982","https://openalex.org/W4205482611","https://openalex.org/W4206554021","https://openalex.org/W4210771532","https://openalex.org/W4225582357","https://openalex.org/W4226038296","https://openalex.org/W4285055292","https://openalex.org/W4285177833","https://openalex.org/W4293193225","https://openalex.org/W4312730569","https://openalex.org/W4313054905","https://openalex.org/W4313590927","https://openalex.org/W4318707911","https://openalex.org/W4321380750","https://openalex.org/W4321770461","https://openalex.org/W4322576316","https://openalex.org/W4376607587","https://openalex.org/W6637242042","https://openalex.org/W6745705539","https://openalex.org/W6804746934","https://openalex.org/W7055499513"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440","https://openalex.org/W2343470940"],"abstract_inverted_index":{"Hyperspectral":[0,60],"anomaly":[1,150],"detection":[2],"(HAD)":[3],"aims":[4],"to":[5,109,157],"identify":[6],"anomalous":[7],"pixels":[8],"in":[9,47,90,94,120],"the":[10,55,65,81,103,111,145,182,193,196],"image":[11],"with":[12],"significant":[13,45],"spectral":[14,33,167],"differences":[15],"from":[16],"their":[17],"surrounding":[18],"background":[19,148,154,161],"pixels,":[20,36],"and":[21,25,39,97,149,162],"has":[22],"important":[23],"military":[24],"civilian":[26],"applications.":[27],"However,":[28],"challenges":[29],"such":[30],"as":[31],"high":[32],"similarity":[34,127],"between":[35,147],"data":[37,119,156,173],"redundancy,":[38],"lack":[40],"of":[41,68,83,113,184,195],"prior":[42],"information":[43],"pose":[44],"difficulties":[46],"HAD.":[48],"To":[49],"address":[50],"these":[51],"issues,":[52],"we":[53,71,101,131],"propose":[54],"Selective":[56],"Siamese":[57,125,135],"Graph":[58],"Guided":[59,79],"Anomaly":[61],"Detection":[62],"method.":[63,197],"In":[64],"initial":[66],"phase":[67],"this":[69,87],"study,":[70],"present":[72],"a":[73,133,141,159],"spatial-spectral":[74],"feature":[75,95],"dynamic":[76],"composition":[77],"module.":[78],"by":[80,123],"principles":[82],"three-way":[84],"clustering":[85],"theories,":[86],"module":[88,138],"excels":[89],"achieving":[91],"heightened":[92],"precision":[93],"embedding":[96],"graph":[98,155],"construction.":[99],"Subsequently,":[100],"introduce":[102],"Characteristic":[104],"Expression":[105],"Differentiation":[106],"mechanism,":[107],"designed":[108],"enhance":[110],"separation":[112],"hidden":[114],"layer":[115],"features":[116],"for":[117],"heterogeneous":[118],"high-dimensional":[121],"space":[122],"incorporating":[124],"network-derived":[126],"discrimination":[128],"principles.":[129],"Lastly,":[130],"develop":[132],"graph-guided":[134],"selective":[136],"reconstruction":[137],"that":[139],"places":[140],"strong":[142],"emphasis":[143],"on":[144,188],"differentiation":[146],"features.":[151],"It":[152],"utilizes":[153],"construct":[158],"pure":[160],"concurrently":[163],"establishes":[164],"connections":[165],"across":[166],"bands.":[168],"This":[169],"approach":[170],"significantly":[171],"enhances":[172],"processing":[174],"efficiency":[175],"while":[176],"reducing":[177],"computational":[178],"resource":[179],"consumption":[180],"through":[181],"elimination":[183],"redundancy.":[185],"Extensive":[186],"experiments":[187],"seven":[189],"public":[190],"datasets":[191],"demonstrate":[192],"effectiveness":[194]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
