{"id":"https://openalex.org/W2586788794","doi":"https://doi.org/10.1109/smc.2016.7844934","title":"Deep convolution neural network with stacks of multi-scale convolutional layer block using triplet of faces for face recognition in the wild","display_name":"Deep convolution neural network with stacks of multi-scale convolutional layer block using triplet of faces for face recognition in the wild","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2586788794","doi":"https://doi.org/10.1109/smc.2016.7844934","mag":"2586788794"},"language":"en","primary_location":{"id":"doi:10.1109/smc.2016.7844934","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2016.7844934","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5055303356","display_name":"Bong-Nam Kang","orcid":"https://orcid.org/0000-0002-6818-7532"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Bong-Nam Kang","raw_affiliation_strings":["Department of Creative IT Engineering, POSTECH, Pohang, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Creative IT Engineering, POSTECH, Pohang, South Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101780915","display_name":"Yonghyun Kim","orcid":"https://orcid.org/0000-0003-0038-7850"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yonghyun Kim","raw_affiliation_strings":["Department of Computer Science & Engineering, POSTECH, Pohang, Sourth Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, POSTECH, Pohang, Sourth Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101431617","display_name":"Daijin Kim","orcid":"https://orcid.org/0000-0002-8046-8521"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daijin Kim","raw_affiliation_strings":["Department of Computer Science & Engineering, POSTECH, Pohang, Sourth Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, POSTECH, Pohang, Sourth Korea","institution_ids":["https://openalex.org/I123900574"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I123900574"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"004460","last_page":"004465"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":1.0,"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/T11448","display_name":"Face recognition and analysis","score":1.0,"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/T10828","display_name":"Biometric Identification and Security","score":0.9961000084877014,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9947999715805054,"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":0.8059327602386475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7862701416015625},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7417618632316589},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7348669767379761},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6918042898178101},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6781215071678162},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6771563291549683},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6376028060913086},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5528973340988159},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4736329913139343},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.46671220660209656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46601346135139465},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4431781768798828},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4303271174430847},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42241087555885315},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0858197808265686}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8059327602386475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7862701416015625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7417618632316589},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7348669767379761},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6918042898178101},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6781215071678162},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6771563291549683},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6376028060913086},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5528973340988159},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4736329913139343},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.46671220660209656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46601346135139465},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4431781768798828},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4303271174430847},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42241087555885315},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0858197808265686},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc.2016.7844934","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2016.7844934","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1509966554","https://openalex.org/W1533861849","https://openalex.org/W1665214252","https://openalex.org/W1782590233","https://openalex.org/W1836465849","https://openalex.org/W1950843348","https://openalex.org/W1975780119","https://openalex.org/W1998808035","https://openalex.org/W2019464758","https://openalex.org/W2024688311","https://openalex.org/W2061430434","https://openalex.org/W2095705004","https://openalex.org/W2096733369","https://openalex.org/W2097117768","https://openalex.org/W2114588272","https://openalex.org/W2121647436","https://openalex.org/W2138451337","https://openalex.org/W2140609507","https://openalex.org/W2144172034","https://openalex.org/W2145287260","https://openalex.org/W2146474141","https://openalex.org/W2153353865","https://openalex.org/W2155893237","https://openalex.org/W2157364932","https://openalex.org/W2950179405","https://openalex.org/W2952304308","https://openalex.org/W2952309299","https://openalex.org/W3099206234","https://openalex.org/W6630649318","https://openalex.org/W6631943919","https://openalex.org/W6637242042","https://openalex.org/W6638667902","https://openalex.org/W6640775171","https://openalex.org/W6674330103","https://openalex.org/W6674914833","https://openalex.org/W6680902425","https://openalex.org/W6681239517"],"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/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374","https://openalex.org/W2964954556"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,22,64],"convolutional":[2],"neural":[3,23,66],"networks":[4,67],"have":[5],"set":[6],"a":[7,42],"new":[8],"trend":[9],"in":[10,56],"fields":[11],"of":[12,54,63],"face":[13,45,74,87],"recognition":[14,46],"by":[15],"improving":[16],"the":[17,61,94,103,107,125],"state-of-the-art":[18],"performance.":[19],"By":[20],"using":[21,47],"networks,":[24],"much":[25],"more":[26],"sophisticated":[27],"and":[28,52,72,83,98],"high":[29],"level":[30],"abstracted":[31],"features":[32,85],"can":[33],"be":[34],"learned":[35],"automatically.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40,92],"propose":[41],"method":[43,118],"for":[44,86],"multi-scale":[48],"convolution":[49,65],"layer":[50],"blocks":[51],"triplets":[53],"faces":[55],"unconstrained":[57],"environments.":[58],"We":[59],"use":[60],"ensemble":[62],"trained":[68,105],"on":[69,124],"differently":[70],"scaled":[71],"aligned":[73],"images.":[75],"This":[76],"extracts":[77],"low":[78],"dimensional":[79],"but":[80],"high-level":[81],"abstraction":[82],"discriminative":[84],"recognition.":[88],"With":[89],"these":[90],"features,":[91],"employ":[93],"jointly":[95],"Bayesian":[96],"model":[97],"transfer":[99],"learning":[100],"which":[101],"adapts":[102],"knowledge":[104],"from":[106],"source":[108],"domain":[109],"to":[110],"target":[111],"domain.":[112],"Experiment":[113],"shows":[114],"that":[115],"our":[116],"proposed":[117],"achieves":[119],"98.33%":[120],"pair-wise":[121],"verification":[122],"accuracy":[123],"LFW":[126],"dataset.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
