{"id":"https://openalex.org/W2971368391","doi":"https://doi.org/10.1109/tip.2019.2938307","title":"Deep Cascade Model-Based Face Recognition: When Deep-Layered Learning Meets Small Data","display_name":"Deep Cascade Model-Based Face Recognition: When Deep-Layered Learning Meets Small Data","publication_year":2019,"publication_date":"2019-09-05","ids":{"openalex":"https://openalex.org/W2971368391","doi":"https://doi.org/10.1109/tip.2019.2938307","mag":"2971368391","pmid":"https://pubmed.ncbi.nlm.nih.gov/31502970"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2938307","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","pubmed"],"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/A5106578837","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-5305-8543"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"funder","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100689700","display_name":"Ji Liu","orcid":"https://orcid.org/0000-0002-0059-4588"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"funder","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Liu","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048088901","display_name":"Bob Zhang","orcid":"https://orcid.org/0000-0003-2497-9519"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"funder","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Bob Zhang","raw_affiliation_strings":["Department of Computer and Information Science, University of Macau, Macau, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100325058","display_name":"David Zhang","orcid":"https://orcid.org/0000-0002-5027-5286"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"David Zhang","raw_affiliation_strings":["School of Science and Engineering, The Chinese University of Hong Kong at Shenzhen, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Science and Engineering, The Chinese University of Hong Kong at Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034427070","display_name":"Ce Zhu","orcid":"https://orcid.org/0000-0001-7607-707X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"funder","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ce Zhu","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.056,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":61,"citation_normalized_percentile":{"value":0.755252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"29","issue":null,"first_page":"1016","last_page":"1029"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991,"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":0.9991,"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/T11448","display_name":"Face recognition and analysis","score":0.998,"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":0.9966,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6430559},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.5975806}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7794025},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.68378025},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6480277},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6430559},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.5975806},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5129804},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42673308},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.42339912},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39683902},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3481446}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2938307","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31502970","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.64,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61771079"}],"datasets":[],"versions":[],"referenced_works_count":63,"referenced_works":["https://openalex.org/W130490334","https://openalex.org/W1504194272","https://openalex.org/W1510982829","https://openalex.org/W1591385104","https://openalex.org/W1600550542","https://openalex.org/W1736339626","https://openalex.org/W1963854021","https://openalex.org/W1974042113","https://openalex.org/W1982405594","https://openalex.org/W1997201895","https://openalex.org/W2000355138","https://openalex.org/W2004544971","https://openalex.org/W2013015287","https://openalex.org/W2014305381","https://openalex.org/W2045079045","https://openalex.org/W2050849575","https://openalex.org/W2065030431","https://openalex.org/W2076363162","https://openalex.org/W2076430826","https://openalex.org/W2085400714","https://openalex.org/W2089685866","https://openalex.org/W2096733369","https://openalex.org/W2097486709","https://openalex.org/W2101149304","https://openalex.org/W2103972604","https://openalex.org/W2108840547","https://openalex.org/W2114748345","https://openalex.org/W2122211032","https://openalex.org/W2123921160","https://openalex.org/W2127271355","https://openalex.org/W2129812935","https://openalex.org/W2132467081","https://openalex.org/W2137659841","https://openalex.org/W2137823674","https://openalex.org/W2141607429","https://openalex.org/W2145152441","https://openalex.org/W2145287260","https://openalex.org/W2155759509","https://openalex.org/W2157069239","https://openalex.org/W2163605009","https://openalex.org/W2164278908","https://openalex.org/W2171837816","https://openalex.org/W2172194783","https://openalex.org/W2194775991","https://openalex.org/W2240559667","https://openalex.org/W2283717164","https://openalex.org/W2293298207","https://openalex.org/W2471678645","https://openalex.org/W2498409055","https://openalex.org/W2517537544","https://openalex.org/W2585551302","https://openalex.org/W2592340788","https://openalex.org/W2770507894","https://openalex.org/W2770824758","https://openalex.org/W2923769473","https://openalex.org/W2949483514","https://openalex.org/W2994340921","https://openalex.org/W3021189487","https://openalex.org/W3099206234","https://openalex.org/W3099438410","https://openalex.org/W3125045090","https://openalex.org/W4231837512","https://openalex.org/W4292363360"],"related_works":["https://openalex.org/W4323060069","https://openalex.org/W4287591324","https://openalex.org/W3170224572","https://openalex.org/W3128220219","https://openalex.org/W3119773509","https://openalex.org/W3108503355","https://openalex.org/W3107204728","https://openalex.org/W3095152779","https://openalex.org/W3006353185","https://openalex.org/W2980176872"],"abstract_inverted_index":{"Sparse":[0],"representation":[1,203],"based":[2,34,135],"classification":[3],"(SRC),":[4],"nuclear-norm":[5],"matrix":[6],"regression":[7],"(NMR),":[8],"and":[9,32,70,121,138,145],"deep":[10,83,131,160],"learning":[11,237],"(DL)":[12],"have":[13,240],"achieved":[14],"a":[15,58,171,215,233],"great":[16],"success":[17],"in":[18,95,124,186,260],"face":[19,150],"recognition":[20],"(FR).":[21],"However,":[22],"there":[23],"still":[24],"exist":[25],"some":[26],"intrinsic":[27],"limitations":[28],"among":[29],"them.":[30],"SRC":[31,120,137],"NMR":[33,139],"coding":[35,49,191],"methods":[36,204],"belong":[37],"to":[38,97,112,241],"one-step":[39],"model,":[40,60],"such":[41],"that":[42,101,235],"the":[43,48,114,193,201,223,226],"latent":[44],"discriminative":[45],"information":[46],"of":[47,82,119,192,217,225],"error":[50],"vector":[51,190],"cannot":[52],"be":[53,206,242],"fully":[54],"exploited.":[55],"DL,":[56],"as":[57],"multi-step":[59],"can":[61,205],"learn":[62],"powerful":[63],"representation,":[64],"but":[65],"relies":[66],"on":[67,88,136,214],"large-scale":[68],"data":[69,90,165],"computation":[71],"resources":[72],"for":[73,105,148,163,177,182],"numerous":[74],"parameters":[75],"training":[76,81],"with":[77,140,195,248],"complicated":[78],"back-propagation.":[79],"Straightforward":[80],"neural":[84,246],"networks":[85],"from":[86],"scratch":[87],"small-scale":[89,164,218],"is":[91,168,175,198,253,258],"almost":[92],"infeasible.":[93],"Therefore,":[94],"order":[96],"develop":[98],"efficient":[99],"algorithms":[100],"are":[102],"specifically":[103],"adapted":[104],"small-scale":[108],"data,":[109],"we":[110,127],"propose":[111,128],"derive":[113],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">deep":[117],"models":[118],"NMR.":[122],"Specifically,":[123],"this":[125],"paper,":[126],"an":[129,158],"end-to-end":[130,159],"cascade":[132,161],"model":[133,162,228],"(DCM)":[134],"hierarchical":[141],"learning,":[142,188],"nonlinear":[143,184],"transformation":[144,185],"multi-layer":[146],"structure":[147,174],"corrupted":[149],"recognition.":[151],"The":[152,255],"contributions":[153],"include":[154],"four":[155],"aspects.":[156],"First,":[157],"without":[166],"back-propagation":[167],"proposed.":[169,199],"Second,":[170],"multi-level":[172],"pyramid":[173],"integrated":[176,208],"local":[178],"feature":[179],"representation.":[180],"Third,":[181],"introducing":[183],"layer-wise":[187],"softmax":[189],"errors":[194],"class":[196],"discrimination":[197],"Fourth,":[200],"existing":[202],"easily":[207],"into":[209],"our":[210],"DCM":[211],"framework.":[212],"Experiments":[213],"number":[216],"benchmark":[219],"FR":[220],"datasets":[221],"demonstrate":[222],"superiority":[224],"proposed":[227],"over":[229],"state-of-the-art":[230],"counterparts.":[231],"Additionally,":[232],"perspective":[234],"deep-layered":[236],"does":[238],"not":[239],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">convolutional":[245],"network":[247],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">back-propagation":[251],"optimization":[252],"consolidated.":[254],"demo":[256],"code":[257],"available":[259],"https://github.com/liuji93/DCM":[263]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2971368391","counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":21}],"updated_date":"2025-04-10T11:52:58.076646","created_date":"2019-09-12"}