{"id":"https://openalex.org/W2090075425","doi":"https://doi.org/10.1109/icmew.2014.6890696","title":"Two dimensional non-negative sparse Partial Least Squares for face recognition","display_name":"Two dimensional non-negative sparse Partial Least Squares for face recognition","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2090075425","doi":"https://doi.org/10.1109/icmew.2014.6890696","mag":"2090075425"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2014.6890696","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2014.6890696","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","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/A5032611421","display_name":"Yongxin Ge","orcid":"https://orcid.org/0000-0003-3266-1009"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongxin Ge","raw_affiliation_strings":["School of Software Engineering, Chongqing University, Chongqing, China","School of Software Engineering, Chongqing University, 400044, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of Software Engineering, Chongqing University, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052560070","display_name":"Sheng Huang","orcid":"https://orcid.org/0000-0001-5610-0826"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Huang","raw_affiliation_strings":["School of Computer Science, Chongqing University, Chongqing, China","School of Computer Science, Chongqing University, 400044, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of Computer Science, Chongqing University, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044044031","display_name":"Xin Feng","orcid":"https://orcid.org/0000-0001-8793-3775"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Feng","raw_affiliation_strings":["College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China","College of Computer Science and Engineering ChongQing, University of Technology, 400054, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]},{"raw_affiliation_string":"College of Computer Science and Engineering ChongQing, University of Technology, 400054, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027821872","display_name":"Jiehui Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115513","display_name":"Xi\u2019an University","ror":"https://ror.org/01zzmf129","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115513"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiehui Zhang","raw_affiliation_strings":["College of Computer Science, Xi'an University of Sicence and Technology, Shanxi, China","College of Computer Science, Xi'an University of Sicence and Technology, Shanxi 710054, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Xi'an University of Sicence and Technology, Shanxi, China","institution_ids":["https://openalex.org/I4210115513"]},{"raw_affiliation_string":"College of Computer Science, Xi'an University of Sicence and Technology, Shanxi 710054, China","institution_ids":["https://openalex.org/I4210115513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103542559","display_name":"Wenbin Bu","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbin Bu","raw_affiliation_strings":["College of Mathematics and Statistics, Chongqing University, Chongqing, China","College of Mathematics and Statistics, Chongqing University, 400044, China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"College of Mathematics and Statistics, Chongqing University, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102013485","display_name":"Dan Yang","orcid":"https://orcid.org/0000-0001-5640-7772"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Yang","raw_affiliation_strings":["School of Software Engineering, Chongqing University, Chongqing, China","School of Software Engineering, Chongqing University, 400044, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of Software Engineering, Chongqing University, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5032611421"],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12868566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"18","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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/T10057","display_name":"Face and Expression Recognition","score":0.9993000030517578,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/robustness","display_name":"Robustness (evolution)","score":0.8073683977127075},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.774304986000061},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6847088932991028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6761629581451416},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6612167358398438},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.6531256437301636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6508932113647461},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5136751532554626},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5072590708732605},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4145733714103699},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2718603014945984}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8073683977127075},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.774304986000061},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6847088932991028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6761629581451416},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6612167358398438},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.6531256437301636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6508932113647461},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5136751532554626},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5072590708732605},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4145733714103699},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2718603014945984},{"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew.2014.6890696","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2014.6890696","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320308380","display_name":"Yale University","ror":"https://ror.org/03v76x132"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W23863644","https://openalex.org/W1830879458","https://openalex.org/W1902027874","https://openalex.org/W1984594863","https://openalex.org/W1996830635","https://openalex.org/W1998938582","https://openalex.org/W2001565863","https://openalex.org/W2029343251","https://openalex.org/W2050834445","https://openalex.org/W2070127246","https://openalex.org/W2078204800","https://openalex.org/W2080296254","https://openalex.org/W2080700960","https://openalex.org/W2097303721","https://openalex.org/W2109675189","https://openalex.org/W2129638195","https://openalex.org/W2132467081","https://openalex.org/W2145096794","https://openalex.org/W2150409012","https://openalex.org/W2160727916","https://openalex.org/W2161655372","https://openalex.org/W2164452299","https://openalex.org/W2164583936","https://openalex.org/W2170917242","https://openalex.org/W2369530636","https://openalex.org/W3124790153","https://openalex.org/W3143596294","https://openalex.org/W4250955649","https://openalex.org/W6676520490","https://openalex.org/W6683703413"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W1973963881","https://openalex.org/W1580457994","https://openalex.org/W2379945344","https://openalex.org/W2912726270","https://openalex.org/W2985118265"],"abstract_inverted_index":{"The":[0],"Partial":[1,53],"Least":[2,54],"Squares":[3,55],"(PLS)":[4],"algorithm":[5,48],"has":[6,133],"been":[7],"widely":[8],"applied":[9],"in":[10,13],"face":[11,120],"recognition":[12,33],"recent":[14],"years.":[15],"However,":[16],"all":[17],"the":[18,32,59,69,76,82,88,105,115,118,125,129],"improved":[19],"algorithms":[20,131],"of":[21,61,91,110],"PLS":[22],"did":[23],"not":[24,73],"utilize":[25],"non-negativity":[26,62],"and":[27,35,63,101,117,132],"sparsity":[28],"synchronously":[29],"to":[30,39,65,136],"improve":[31],"accuracy":[34],"robustness.":[36],"In":[37],"order":[38],"solve":[40],"these":[41],"problems,":[42],"this":[43],"paper":[44],"proposes":[45],"a":[46,108],"novel":[47],"named":[49],"Two-Dimension":[50],"Non-negative":[51],"Sparse":[52],"(2DNSPLS),":[56],"which":[57,122],"incorporates":[58],"constraints":[60],"sparse":[64],"2DPLS":[66],"while":[67],"extracting":[68],"facial":[70],"features.":[71],"Consequently,":[72],"only":[74],"do":[75],"features":[77],"extracted":[78],"by":[79],"2DNSPLS":[80],"contain":[81,97],"label":[83],"information,":[84],"as":[85,87],"well":[86],"internal":[89],"structure":[90],"image":[92],"matrix,":[93],"but":[94],"they":[95],"also":[96],"local":[98],"non-negative":[99],"interpretability":[100],"sparsity.":[102],"For":[103],"evaluating":[104],"approach's":[106],"performance,":[107],"series":[109],"experiments":[111],"are":[112],"conducted":[113],"on":[114],"Yale":[116],"PIE":[119],"databases,":[121],"demonstrate":[123],"that":[124],"proposed":[126],"approach":[127],"outperforms":[128],"state-of-art":[130],"good":[134],"robustness":[135],"occlusion.":[137]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
