{"id":"https://openalex.org/W4292347924","doi":"https://doi.org/10.1109/access.2022.3200482","title":"Multi-Scale Deep Subspace Clustering With Discriminative Learning","display_name":"Multi-Scale Deep Subspace Clustering With Discriminative Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4292347924","doi":"https://doi.org/10.1109/access.2022.3200482"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3200482","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3200482","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09863835.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09863835.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054441969","display_name":"Jiao Wang","orcid":"https://orcid.org/0000-0003-3597-0042"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Wang","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":"https://orcid.org/0000-0003-3597-0042","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101512414","display_name":"Bin Wu","orcid":"https://orcid.org/0000-0002-4976-8956"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wu","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068223297","display_name":"Zhenwen Ren","orcid":"https://orcid.org/0000-0003-3791-9750"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenwen Ren","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]},{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102808416","display_name":"Yunhui Zhou","orcid":"https://orcid.org/0000-0001-8691-4847"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhui Zhou","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0153,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.77044489,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"91283","last_page":"91293"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7318313121795654},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.709945559501648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6673198342323303},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6435227394104004},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5449258089065552},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5115659832954407},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.47176888585090637},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4465329051017761},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3215627670288086},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.06401047110557556},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.059306055307388306}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7318313121795654},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.709945559501648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6673198342323303},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6435227394104004},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5449258089065552},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5115659832954407},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.47176888585090637},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4465329051017761},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3215627670288086},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.06401047110557556},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.059306055307388306}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3200482","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3200482","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09863835.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:313572a0a00d40f196dfa15e71f446c8","is_oa":true,"landing_page_url":"https://doaj.org/article/313572a0a00d40f196dfa15e71f446c8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 91283-91293 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3200482","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3200482","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09863835.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7799999713897705,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3048430157","display_name":null,"funder_award_id":"62106209","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4729467532","display_name":null,"funder_award_id":"KFKT2021B23","funder_id":"https://openalex.org/F4320326895","funder_display_name":"State Key Laboratory of Novel Software Technology"},{"id":"https://openalex.org/G5636702253","display_name":null,"funder_award_id":"KFKT2021B23","funder_id":"https://openalex.org/F4320324852","funder_display_name":"Nanjing University"},{"id":"https://openalex.org/G6518553514","display_name":null,"funder_award_id":"2021YJ0083","funder_id":"https://openalex.org/F4320333335","funder_display_name":"Sichuan Province Science and Technology Support Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322559","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474"},{"id":"https://openalex.org/F4320323711","display_name":"Southwest University","ror":"https://ror.org/01kj4z117"},{"id":"https://openalex.org/F4320324852","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760"},{"id":"https://openalex.org/F4320326895","display_name":"State Key Laboratory of Novel Software Technology","ror":null},{"id":"https://openalex.org/F4320333335","display_name":"Sichuan Province Science and Technology Support Program","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4292347924.pdf","grobid_xml":"https://content.openalex.org/works/W4292347924.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1981458038","https://openalex.org/W1992300915","https://openalex.org/W1993962865","https://openalex.org/W2003217181","https://openalex.org/W2017441234","https://openalex.org/W2118858274","https://openalex.org/W2151155403","https://openalex.org/W2177347332","https://openalex.org/W2546325542","https://openalex.org/W2555332322","https://openalex.org/W2752782242","https://openalex.org/W2759684359","https://openalex.org/W2798534672","https://openalex.org/W2808847899","https://openalex.org/W2809034148","https://openalex.org/W2809955885","https://openalex.org/W2893830906","https://openalex.org/W2911651175","https://openalex.org/W2954752948","https://openalex.org/W2963051348","https://openalex.org/W2963840432","https://openalex.org/W2964169082","https://openalex.org/W2964837208","https://openalex.org/W2972882412","https://openalex.org/W2979685515","https://openalex.org/W3000966862","https://openalex.org/W3003312910","https://openalex.org/W3010186256","https://openalex.org/W3035059937","https://openalex.org/W3039121139","https://openalex.org/W3046905751","https://openalex.org/W3092273613","https://openalex.org/W3112110305","https://openalex.org/W3119694480","https://openalex.org/W3143649444","https://openalex.org/W3155625688","https://openalex.org/W3157795475","https://openalex.org/W3160132661","https://openalex.org/W3165527726","https://openalex.org/W3177052299","https://openalex.org/W3183607039","https://openalex.org/W3208415928","https://openalex.org/W4210353804","https://openalex.org/W4214814755","https://openalex.org/W4250657332","https://openalex.org/W6603183647","https://openalex.org/W6744043827","https://openalex.org/W6744987142","https://openalex.org/W6758292543","https://openalex.org/W6761583371","https://openalex.org/W6785581017"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"Deep":[0],"subspace":[1,36,77,162],"clustering":[2,7,12,78],"methods":[3,17],"have":[4,173],"achieved":[5],"impressive":[6],"performance":[8],"compared":[9,179],"with":[10,79,139,180],"other":[11],"algorithms.":[13],"However,":[14],"most":[15],"existing":[16],"suffer":[18],"from":[19,106],"the":[20,27,32,42,53,112,120,123,149,155,168,175],"following":[21],"problems:":[22],"1)":[23],"they":[24,40,51],"only":[25],"consider":[26],"global":[28,107],"features":[29,34,160],"but":[30],"neglect":[31,41],"local":[33,109],"in":[35,60,68],"self-expressiveness":[37,47,87,103,125,163],"learning;":[38],"2)":[39],"discriminative":[43,80,131],"information":[44,59],"of":[45,122,177],"each":[46,134],"coefficient":[48,88,104,126],"matrix;":[49],"3)":[50],"ignore":[52],"useful":[54],"long-range":[55,156],"dependencies":[56,157],"and":[57,98,108,136,158,170],"positional":[58,159],"feature":[61],"representation":[62,145],"learning.":[63,164],"To":[64],"solve":[65],"these":[66],"problems,":[67],"this":[69],"paper,":[70],"we":[71],"propose":[72],"a":[73,85],"novel":[74],"multi-scale":[75,102,124],"deep":[76],"learning":[81],"(MDSCDL)":[82],"to":[83,100,143,153],"obtain":[84],"high-quality":[86],"matrix.":[89],"Specifically,":[90],"MDSCDL":[91,128,147,178],"bridges":[92],"multiple":[93],"fully-connection":[94],"layers":[95],"between":[96],"encoder":[97],"decoder":[99],"learn":[101],"matrices":[105],"features,":[110],"representing":[111],"more":[113],"comprehensive":[114],"relationship":[115],"among":[116],"data.":[117],"By":[118],"modeling":[119],"interdependencies":[121],"matrices,":[127],"adaptively":[129],"assigns":[130],"weights":[132],"for":[133,161],"matrix":[135],"fuses":[137],"them":[138],"convolution":[140],"operation.":[141],"Moreover,":[142],"increase":[144],"power,":[146],"introduces":[148],"coordinate":[150],"attention":[151],"mechanism":[152],"extract":[154],"Extensive":[165],"experiments":[166],"on":[167],"face":[169],"object":[171],"datasets":[172],"shown":[174],"superiority":[176],"several":[181],"state-of-the-art":[182],"methods.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
