{"id":"https://openalex.org/W4413088586","doi":"https://doi.org/10.1049/ipr2.70157","title":"Subspace\u2010Guided Feature Reconstruction for Unsupervised Anomaly Localization","display_name":"Subspace\u2010Guided Feature Reconstruction for Unsupervised Anomaly Localization","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413088586","doi":"https://doi.org/10.1049/ipr2.70157"},"language":"en","primary_location":{"id":"doi:10.1049/ipr2.70157","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70157","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/ipr2.70157","source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/ipr2.70157","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016255943","display_name":"Katsuya Hotta","orcid":"https://orcid.org/0000-0002-8148-1445"},"institutions":[{"id":"https://openalex.org/I173009982","display_name":"Iwate University","ror":"https://ror.org/04cd75h10","country_code":"JP","type":"education","lineage":["https://openalex.org/I173009982"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Katsuya Hotta","raw_affiliation_strings":["Iwate University Morioka\u2010shi Iwate Japan"],"raw_orcid":"https://orcid.org/0000-0002-8148-1445","affiliations":[{"raw_affiliation_string":"Iwate University Morioka\u2010shi Iwate Japan","institution_ids":["https://openalex.org/I173009982"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089283853","display_name":"Chao Zhang","orcid":"https://orcid.org/0000-0002-0845-9217"},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chao Zhang","raw_affiliation_strings":["University of Toyama Toyama\u2010shi Toyama Japan"],"raw_orcid":"https://orcid.org/0000-0002-0845-9217","affiliations":[{"raw_affiliation_string":"University of Toyama Toyama\u2010shi Toyama Japan","institution_ids":["https://openalex.org/I42766147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112268554","display_name":"Yoshihiro Hagihara","orcid":null},"institutions":[{"id":"https://openalex.org/I173009982","display_name":"Iwate University","ror":"https://ror.org/04cd75h10","country_code":"JP","type":"education","lineage":["https://openalex.org/I173009982"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshihiro Hagihara","raw_affiliation_strings":["Iwate University Morioka\u2010shi Iwate Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Iwate University Morioka\u2010shi Iwate Japan","institution_ids":["https://openalex.org/I173009982"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045648943","display_name":"Takuya Akashi","orcid":"https://orcid.org/0000-0001-9177-7306"},"institutions":[{"id":"https://openalex.org/I136446963","display_name":"Okayama University of Science","ror":"https://ror.org/05aevyc10","country_code":"JP","type":"education","lineage":["https://openalex.org/I136446963"]},{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]},{"id":"https://openalex.org/I4210100185","display_name":"Okayama University Hospital","ror":"https://ror.org/019tepx80","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210100185"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuya Akashi","raw_affiliation_strings":["Okayama University Kita\u2010ku Okayama Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Okayama University Kita\u2010ku Okayama Japan","institution_ids":["https://openalex.org/I136446963","https://openalex.org/I163770644","https://openalex.org/I4210100185"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016255943"],"corresponding_institution_ids":["https://openalex.org/I173009982"],"apc_list":{"value":2000,"currency":"EUR","value_usd":2200},"apc_paid":{"value":2000,"currency":"EUR","value_usd":2200},"fwci":5.7171,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.95820501,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"19","issue":"1","first_page":"e70157","last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.975600004196167,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9649999737739563,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.7647842168807983},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6929028034210205},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6799511909484863},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.6645033359527588},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6573101282119751},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.642688512802124},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5216701030731201},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5016641616821289},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48853740096092224},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4684256315231323},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14927852153778076}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7647842168807983},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6929028034210205},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6799511909484863},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.6645033359527588},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6573101282119751},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.642688512802124},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5216701030731201},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5016641616821289},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48853740096092224},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4684256315231323},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14927852153778076},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1049/ipr2.70157","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70157","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/ipr2.70157","source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"},{"id":"pmh:oai:irdb.nii.ac.jp:01081:0007225674","is_oa":true,"landing_page_url":"https://ousar.lib.okayama-u.ac.jp/69896","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IET Image Processing","raw_type":"journal article"}],"best_oa_location":{"id":"doi:10.1049/ipr2.70157","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70157","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/ipr2.70157","source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.4099999964237213}],"awards":[{"id":"https://openalex.org/G6708979853","display_name":null,"funder_award_id":"JP24K20828","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8391613456","display_name":null,"funder_award_id":"JP23K19989","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413088586.pdf","grobid_xml":"https://content.openalex.org/works/W4413088586.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W1540596182","https://openalex.org/W1554085250","https://openalex.org/W1821462560","https://openalex.org/W1826223126","https://openalex.org/W1967456674","https://openalex.org/W1993962865","https://openalex.org/W2050834445","https://openalex.org/W2108598243","https://openalex.org/W2116148865","https://openalex.org/W2128659236","https://openalex.org/W2134474909","https://openalex.org/W2194775991","https://openalex.org/W2247953682","https://openalex.org/W2809705434","https://openalex.org/W2888407265","https://openalex.org/W2946948417","https://openalex.org/W2948982773","https://openalex.org/W2963045681","https://openalex.org/W2963610939","https://openalex.org/W2963840432","https://openalex.org/W2964137095","https://openalex.org/W2978971541","https://openalex.org/W3013379031","https://openalex.org/W3023868590","https://openalex.org/W3034314048","https://openalex.org/W3092704883","https://openalex.org/W3112381459","https://openalex.org/W3118895125","https://openalex.org/W3147184966","https://openalex.org/W3156880769","https://openalex.org/W3169651898","https://openalex.org/W3204520143","https://openalex.org/W3209793239","https://openalex.org/W3214308028","https://openalex.org/W4212874935","https://openalex.org/W4214694907","https://openalex.org/W4224861804","https://openalex.org/W4250657332","https://openalex.org/W4280595078","https://openalex.org/W4286750617","https://openalex.org/W4287887190","https://openalex.org/W4289792391","https://openalex.org/W4312239247","https://openalex.org/W4312605624","https://openalex.org/W4312772600","https://openalex.org/W4312933868","https://openalex.org/W4316035795","https://openalex.org/W4362471962","https://openalex.org/W4376626035","https://openalex.org/W4386065608","https://openalex.org/W4386065890","https://openalex.org/W4386629859","https://openalex.org/W4389267285","https://openalex.org/W4390872231","https://openalex.org/W4392402285","https://openalex.org/W4402039215","https://openalex.org/W4402716302","https://openalex.org/W4411244487","https://openalex.org/W6632267817","https://openalex.org/W6642206748","https://openalex.org/W6690901460"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W4289378085","https://openalex.org/W4294291164","https://openalex.org/W3172436493","https://openalex.org/W1887135636","https://openalex.org/W4287164812","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849"],"abstract_inverted_index":{"ABSTRACT":[0],"Unsupervised":[1],"anomaly":[2,95,197],"localization":[3,198],"aims":[4],"to":[5,36,72,75,89,100,112,149,171,180],"identify":[6],"anomalous":[7],"regions":[8],"that":[9,160,191],"deviate":[10],"from":[11,104],"normal":[12],"sample":[13,26],"patterns.":[14],"Most":[15],"recent":[16],"methods":[17,57],"perform":[18],"feature":[19,86,92,169],"matching":[20],"or":[21],"reconstruction":[22,87,170],"for":[23,94],"the":[24,41,46,62,67,105,114,122,127,135,139,142,152,162,168],"target":[25,117],"with":[27],"pre\u2010trained":[28],"deep":[29,42,116],"neural":[30],"networks.":[31],"However,":[32],"they":[33],"still":[34],"struggle":[35],"address":[37],"challenging":[38],"anomalies":[39],"because":[40],"embeddings":[43],"stored":[44,65],"in":[45,66,138],"memory":[47,68,140,182],"bank":[48],"can":[49,145],"be":[50,146],"less":[51,181],"powerful":[52],"and":[53,109,166],"informative.":[54],"Specifically,":[55],"prior":[56],"often":[58],"overly":[59],"rely":[60],"on":[61,174,186],"finite":[63],"resources":[64,137],"bank,":[69,141],"which":[70],"leads":[71],"low":[73],"robustness":[74],"unseen":[76],"targets.":[77],"In":[78],"this":[79],"paper,":[80],"we":[81,155],"propose":[82,156],"a":[83,157,175],"novel":[84],"subspace\u2010guided":[85],"framework":[88],"pursue":[90],"adaptive":[91],"approximation":[93],"localization.":[96],"It":[97],"first":[98],"learns":[99,111],"construct":[101],"low\u2010dimensional":[102],"subspaces":[103,165],"given":[106,115],"nominal":[107],"samples,":[108],"then":[110],"reconstruct":[113],"embedding":[118],"by":[119],"linearly":[120],"combining":[121],"subspace":[123],"basis":[124],"vectors":[125],"using":[126],"self\u2010expressive":[128],"model.":[129],"Our":[130],"core":[131],"is":[132],"that,":[133],"despite":[134],"limited":[136],"out\u2010of\u2010bank":[143],"features":[144],"alternatively":[147],"\u201cmimicked\u201d":[148],"adaptively":[150],"model":[151],"target.":[153],"Moreover,":[154],"sampling":[158],"method":[159],"leverages":[161],"sparsity":[163],"of":[164],"allows":[167],"depend":[172],"only":[173],"small":[176],"resource":[177],"subset,":[178],"contributing":[179],"overhead.":[183],"Extensive":[184],"experiments":[185],"three":[187],"benchmark":[188],"datasets":[189],"demonstrate":[190],"our":[192],"approach":[193],"generally":[194],"achieves":[195],"state\u2010of\u2010the\u2010art":[196],"performance.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}