{"id":"https://openalex.org/W4378194596","doi":"https://doi.org/10.1109/tgrs.2023.3279834","title":"LRR-Net: An Interpretable Deep Unfolding Network for Hyperspectral Anomaly Detection","display_name":"LRR-Net: An Interpretable Deep Unfolding Network for Hyperspectral Anomaly Detection","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4378194596","doi":"https://doi.org/10.1109/tgrs.2023.3279834"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3279834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3279834","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/A5100354331","display_name":"Chenyu Li","orcid":"https://orcid.org/0000-0002-1687-9676"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chenyu Li","raw_affiliation_strings":["School of Mathematics and Statistics, Southeast University, Nanjing, China","Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389658","display_name":"Bing Zhang","orcid":"https://orcid.org/0000-0001-7311-9844"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Zhang","raw_affiliation_strings":["School of Mathematics and Statistics, Southeast University, Nanjing, China","Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075013625","display_name":"Danfeng Hong","orcid":"https://orcid.org/0000-0002-3212-9584"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danfeng Hong","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013885739","display_name":"Jing Yao","orcid":"https://orcid.org/0000-0003-1301-9758"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yao","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN","FR"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["INRIA, CNRS, Grenoble INP, GIPSA-Laboratory, Universit&#x00E9; Grenoble Alpes, Grenoble, France","Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"INRIA, CNRS, Grenoble INP, GIPSA-Laboratory, Universit&#x00E9; Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210124956","https://openalex.org/I1326498283","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100354331"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199","https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":40.3883,"has_fulltext":false,"cited_by_count":254,"citation_normalized_percentile":{"value":0.99861741,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"12"},"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":0.9902999997138977,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.975600004196167,"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/computer-science","display_name":"Computer science","score":0.7865138053894043},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7379720211029053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6712656021118164},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6110032796859741},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6030219793319702},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5531238913536072},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4976058304309845},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4601919949054718},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.45017290115356445},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4416913390159607},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.41970810294151306},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3490205407142639},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09077754616737366}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7865138053894043},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7379720211029053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6712656021118164},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6110032796859741},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6030219793319702},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5531238913536072},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4976058304309845},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4601919949054718},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.45017290115356445},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4416913390159607},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.41970810294151306},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3490205407142639},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09077754616737366},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2023.3279834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3279834","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"},{"id":"pmh:oai:HAL:hal-04473647v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04473647","pdf_url":null,"source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing, 2023, 61, pp.1-12. &#x27E8;10.1109/TGRS.2023.3279834&#x27E9;","raw_type":"Journal articles"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5484287860","display_name":null,"funder_award_id":"42271350","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6629202286","display_name":null,"funder_award_id":"2022YFB3903401","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G993160810","display_name":null,"funder_award_id":"42241109","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"},{"id":"https://openalex.org/F4320321048","display_name":"AXA Research Fund","ror":"https://ror.org/02zxqxw53"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1970099214","https://openalex.org/W1997201895","https://openalex.org/W2004491663","https://openalex.org/W2010702969","https://openalex.org/W2010797000","https://openalex.org/W2024288510","https://openalex.org/W2042442393","https://openalex.org/W2047519171","https://openalex.org/W2047870694","https://openalex.org/W2067782748","https://openalex.org/W2097381359","https://openalex.org/W2118103795","https://openalex.org/W2124463804","https://openalex.org/W2163816481","https://openalex.org/W2167320870","https://openalex.org/W2288752886","https://openalex.org/W2295576075","https://openalex.org/W2497075055","https://openalex.org/W2548234276","https://openalex.org/W2755992512","https://openalex.org/W2764207251","https://openalex.org/W2807662216","https://openalex.org/W2833324965","https://openalex.org/W2900199428","https://openalex.org/W2902719825","https://openalex.org/W2914736033","https://openalex.org/W2951085447","https://openalex.org/W2963284277","https://openalex.org/W2969635036","https://openalex.org/W2983563481","https://openalex.org/W3003955104","https://openalex.org/W3007076381","https://openalex.org/W3015126059","https://openalex.org/W3047443805","https://openalex.org/W3100714546","https://openalex.org/W3103695279","https://openalex.org/W3107702424","https://openalex.org/W3137199127","https://openalex.org/W3170878188","https://openalex.org/W3172610471","https://openalex.org/W3199351457","https://openalex.org/W3206450719","https://openalex.org/W4224261559","https://openalex.org/W4292363360","https://openalex.org/W4313506322","https://openalex.org/W4327662581","https://openalex.org/W4387623802","https://openalex.org/W6675164516","https://openalex.org/W6677645113","https://openalex.org/W6838209734"],"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":{"Considerable":[0],"endeavors":[1],"have":[2],"been":[3],"expended":[4],"towards":[5],"enhancing":[6],"the":[7,27,53,80,89,99,105,111,116,123,130,136,153,156,166,171],"representation":[8],"performance":[9],"for":[10,35,40,138],"Hyperspectral":[11],"Anomaly":[12],"Detection":[13],"(HAD)":[14],"through":[15],"physical":[16],"model-based":[17],"methods":[18],"and":[19,42,59,103,168],"recent":[20],"deep":[21,84,112,131],"learning-based":[22],"approaches.":[23],"Of":[24],"these":[25],"methods,":[26],"Low-Rank":[28],"Representation":[29],"(LRR)":[30],"model":[31,82,101],"is":[32],"widely":[33],"adopted":[34],"its":[36,46],"formidable":[37],"separation":[38],"capabilities":[39],"background":[41],"target":[43],"features,":[44],"however,":[45],"practical":[47],"applications":[48],"are":[49],"limited":[50],"due":[51],"to":[52,75,97,114,151,175],"reliance":[54],"on":[55,161],"manual":[56,139],"parameter":[57,140],"selection":[58],"subpar":[60],"generalization":[61],"performance.":[62],"To":[63],"this":[64,66,143],"end,":[65],"paper":[67,144],"presents":[68],"a":[69,146],"new":[70],"HAD":[71],"baseline":[72],"network,":[73,133],"referred":[74],"as":[76,107],"LRR-Net,":[77],"which":[78],"synergizes":[79],"LRR":[81,100],"with":[83],"learning":[85],"techniques.":[86],"LRR-Net":[87,121,157],"leverages":[88],"alternating":[90],"direction":[91],"method":[92],"of":[93,118,129,155,170],"multipliers":[94],"(ADMM)":[95],"optimizer":[96],"solve":[98],"efficiently":[102],"incorporates":[104],"solution":[106],"prior":[108],"knowledge":[109],"into":[110,126],"network":[113,149],"guide":[115],"optimization":[117],"parameters.":[119],"Moreover,":[120],"transforms":[122],"regularized":[124],"parameters":[125,128],"trainable":[127],"neural":[132,148],"thus":[134],"alleviating":[135],"need":[137],"tuning.":[141],"Additionally,":[142],"proposes":[145],"sparse":[147],"embedding":[150],"demonstrate":[152],"scalability":[154],"framework.":[158],"Empirical":[159],"evaluations":[160],"eight":[162],"distinct":[163],"datasets":[164],"illustrate":[165],"efficacy":[167],"superiority":[169],"proposed":[172],"approach":[173],"compared":[174],"state-of-the-art":[176],"methods.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":66},{"year":2024,"cited_by_count":139},{"year":2023,"cited_by_count":42}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
