{"id":"https://openalex.org/W2415248485","doi":"https://doi.org/10.1109/acpr.2015.7486492","title":"Transposed discriminative low-rank representation for face recognition","display_name":"Transposed discriminative low-rank representation for face recognition","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2415248485","doi":"https://doi.org/10.1109/acpr.2015.7486492","mag":"2415248485"},"language":"en","primary_location":{"id":"doi:10.1109/acpr.2015.7486492","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486492","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","raw_type":"proceedings-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/A5103009100","display_name":"Hoang Vu Nguyen","orcid":"https://orcid.org/0009-0003-9053-3221"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hoangvu Nguyen","raw_affiliation_strings":["Faculty of Industrial Engineering, Tien Giang University, My Tho, Viet Nam"],"affiliations":[{"raw_affiliation_string":"Faculty of Industrial Engineering, Tien Giang University, My Tho, Viet Nam","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100883743","display_name":"Wankou Yang","orcid":null},"institutions":[{"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":"Wankou Yang","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019248683","display_name":"Changyin Sun","orcid":"https://orcid.org/0000-0001-9269-334X"},"institutions":[{"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":"Changyin Sun","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103009100"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21997588,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"191","last_page":"195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"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":0.9991999864578247,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.984499990940094,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.9434559345245361},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7819958329200745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.734354555606842},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7332760095596313},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6301940679550171},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5829553008079529},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5683839917182922},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4742542803287506},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4534067213535309},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.41380053758621216},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34846824407577515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10713061690330505}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9434559345245361},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7819958329200745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.734354555606842},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7332760095596313},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6301940679550171},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5829553008079529},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5683839917182922},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4742542803287506},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4534067213535309},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.41380053758621216},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34846824407577515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10713061690330505},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acpr.2015.7486492","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486492","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W1510147702","https://openalex.org/W1916598143","https://openalex.org/W1963854021","https://openalex.org/W1989550328","https://openalex.org/W1997201895","https://openalex.org/W2000355138","https://openalex.org/W2013015287","https://openalex.org/W2021770241","https://openalex.org/W2043360443","https://openalex.org/W2058294968","https://openalex.org/W2079451958","https://openalex.org/W2097622337","https://openalex.org/W2100549954","https://openalex.org/W2103972604","https://openalex.org/W2123921160","https://openalex.org/W2125874614","https://openalex.org/W2129812935","https://openalex.org/W2131628350","https://openalex.org/W2137358782","https://openalex.org/W2951085447","https://openalex.org/W2994340921","https://openalex.org/W6603183647","https://openalex.org/W6635552349","https://openalex.org/W6647761816","https://openalex.org/W6649529986","https://openalex.org/W6661611307","https://openalex.org/W6675164516","https://openalex.org/W6679973066","https://openalex.org/W6680112705"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374","https://openalex.org/W2981954115","https://openalex.org/W2901057123"],"abstract_inverted_index":{"In":[0,77],"this":[1],"paper,":[2],"based":[3],"on":[4,102],"Low-rank":[5],"Representation":[6,16],"(LRR)":[7],"we":[8,38],"present":[9],"a":[10,32,40,87],"new":[11],"method,":[12],"Transposed":[13],"Discriminative":[14],"Low-Rank":[15],"(TDLRR),":[17],"for":[18,75],"face":[19,105],"recognition":[20],"in":[21],"which":[22],"both":[23],"training":[24,98],"and":[25,95,110],"testing":[26],"images":[27],"are":[28,82],"corrupted.":[29],"By":[30],"adding":[31],"discriminative":[33,48],"term":[34],"into":[35],"LRR":[36,53],"function,":[37],"obtained":[39],"low-rank":[41,88],"matrix":[42,90],"recovery":[43,93],"with":[44],"the":[45,47,62,79,92,96,108],"increase":[46],"ability":[49],"between":[50,91],"different":[51],"classes.":[52],"of":[54,65,112],"transposed":[55],"data":[56,68],"is":[57],"also":[58,83],"applied":[59],"to":[60,71],"extract":[61],"salient":[63],"features":[64,74],"these":[66],"recovered":[67],"so":[69],"as":[70],"produce":[72],"effective":[73],"classification.":[76],"addition,":[78],"test":[80],"samples":[81],"corrected":[84],"by":[85],"using":[86],"projection":[89],"results":[94,101],"original":[97],"samples.":[99],"Experimental":[100],"three":[103],"popular":[104],"databases":[106],"demonstrate":[107],"effectiveness":[109],"robustness":[111],"our":[113],"method.":[114]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}