{"id":"https://openalex.org/W2998816058","doi":"https://doi.org/10.1145/3341161.3343525","title":"Deep learning based estimation of facial attributes on challenging mobile phone face datasets","display_name":"Deep learning based estimation of facial attributes on challenging mobile phone face datasets","publication_year":2019,"publication_date":"2019-08-27","ids":{"openalex":"https://openalex.org/W2998816058","doi":"https://doi.org/10.1145/3341161.3343525","mag":"2998816058"},"language":"en","primary_location":{"id":"doi:10.1145/3341161.3343525","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341161.3343525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","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/A5012893167","display_name":"J. Dafni Rose","orcid":"https://orcid.org/0000-0002-2715-3651"},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacob Rose","raw_affiliation_strings":["West Virginia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"West Virginia University","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056462004","display_name":"Thirimachos Bourlai","orcid":"https://orcid.org/0000-0001-8751-0836"},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thirimachos Bourlai","raw_affiliation_strings":["West Virginia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"West Virginia University","institution_ids":["https://openalex.org/I12097938"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I12097938"],"apc_list":null,"apc_paid":null,"fwci":0.366,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.67423148,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1120","last_page":"1127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9993000030517578,"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":0.9980000257492065,"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":0.8497213125228882},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6986989974975586},{"id":"https://openalex.org/keywords/authentication","display_name":"Authentication (law)","score":0.6962102651596069},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6923156380653381},{"id":"https://openalex.org/keywords/mobile-phone","display_name":"Mobile phone","score":0.5711278319358826},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5705412030220032},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5514088273048401},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5268688797950745},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.5206798315048218},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5150437355041504},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.487872838973999},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4701806604862213},{"id":"https://openalex.org/keywords/three-dimensional-face-recognition","display_name":"Three-dimensional face recognition","score":0.4386475682258606},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37522387504577637},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3606603145599365},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.17699047923088074}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8497213125228882},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6986989974975586},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.6962102651596069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6923156380653381},{"id":"https://openalex.org/C2777421447","wikidata":"https://www.wikidata.org/wiki/Q17517","display_name":"Mobile phone","level":2,"score":0.5711278319358826},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5705412030220032},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5514088273048401},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5268688797950745},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.5206798315048218},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5150437355041504},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.487872838973999},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4701806604862213},{"id":"https://openalex.org/C88799230","wikidata":"https://www.wikidata.org/wiki/Q3398329","display_name":"Three-dimensional face recognition","level":5,"score":0.4386475682258606},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37522387504577637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3606603145599365},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.17699047923088074},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3341161.3343525","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341161.3343525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1534477342","https://openalex.org/W1594031697","https://openalex.org/W1782590233","https://openalex.org/W1834627138","https://openalex.org/W1946323491","https://openalex.org/W1967320885","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2119821739","https://openalex.org/W2128560777","https://openalex.org/W2132123667","https://openalex.org/W2147414309","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2164598857","https://openalex.org/W2217289705","https://openalex.org/W2341528187","https://openalex.org/W2367822705","https://openalex.org/W2440599146","https://openalex.org/W2536626143","https://openalex.org/W2549401308","https://openalex.org/W2564534737","https://openalex.org/W2579578355","https://openalex.org/W2604272474","https://openalex.org/W2729265300","https://openalex.org/W2769710461","https://openalex.org/W2775447965","https://openalex.org/W2793708128","https://openalex.org/W2798685991","https://openalex.org/W2807735086","https://openalex.org/W2884669884","https://openalex.org/W2963152987","https://openalex.org/W2963592586","https://openalex.org/W2964118024","https://openalex.org/W3013865655","https://openalex.org/W3101998545","https://openalex.org/W4239510810","https://openalex.org/W4297957988"],"related_works":["https://openalex.org/W2166031825","https://openalex.org/W2918845005","https://openalex.org/W2040482211","https://openalex.org/W2058325696","https://openalex.org/W2185537520","https://openalex.org/W325114128","https://openalex.org/W4285815683","https://openalex.org/W2336272890","https://openalex.org/W4312238398","https://openalex.org/W4308999963"],"abstract_inverted_index":{"Facial":[0],"attribute":[1,277],"analysis":[2],"is":[3,23,37,69,124,138,153],"an":[4,58,102],"important":[5],"step":[6],"in":[7,28,87,251],"many":[8],"biometric":[9,34],"algorithms,":[10],"including":[11],"face":[12,21,84,148,173,233],"recognition":[13,85],"based":[14,30,221],"human":[15],"authentication.":[16],"Detecting":[17],"the":[18,44,48,54,110,163,179,185,210,276,282],"state":[19],"of":[20,47,73,112,158,209,271],"attributes":[22,75,144],"becoming":[24],"even":[25],"more":[26],"popular":[27],"mobile":[29,243],"applications,":[31],"where":[32],"a":[33,70,83,113,122,134,154],"authentication":[35,105,181],"application":[36],"used":[38,286],"to":[39,61,65,81,203,266],"quickly":[40],"and":[41,51,104,205,218,227,231,242,284,289],"accurately":[42],"verify":[43],"claimed":[45],"identity":[46],"owners":[49],"device,":[50],"also,":[52],"keep":[53],"device":[55],"secure":[56],"if":[57],"intruder":[59],"attempts":[60,199],"gain":[62],"unauthorized":[63],"access":[64],"it.":[66],"While":[67],"there":[68],"large":[71],"number":[72],"facial":[74,136,212],"that":[76,97],"can":[77,177],"be":[78],"automatically":[79,204],"detected":[80],"support":[82],"system,":[86],"this":[88],"paper":[89],"we":[90,176,214],"focus":[91],"on":[92,229,275],"detecting":[93,132],"three":[94],"specific":[95],"ones":[96],"are":[98,115,145,225,262],"useful":[99,156],"during":[100,166,200],"both":[101,216],"enrollment":[103],"process:":[106],"(1)":[107],"determining":[108,120],"whether":[109,121,133],"eyes":[111],"subject":[114,123],"open":[116],"or":[117,127,141,254],"closed,":[118],"(2)":[119],"wearing":[125],"glasses":[126],"not,":[128],"and,":[129],"finally,":[130],"(3)":[131],"subjects":[135],"pose":[137],"either":[139,252],"frontal":[140],"non-frontal.":[142],"These":[143,223],"associated":[146],"with":[147],"image":[149,174,234],"quality":[150,172],"control,":[151],"which":[152],"very":[155],"component":[157],"modern":[159],"FR":[160],"systems":[161],"under":[162],"following":[164],"context:":[165],"live":[167],"authentication,":[168],"by":[169],"limiting":[170],"low":[171],"data,":[175],"enhance":[178],"face-based":[180],"accuracy,":[182],"while":[183],"at":[184,247],"same":[186],"time":[187],"improve":[188],"user":[189],"satisfaction":[190],"via":[191],"improved":[192],"system":[193],"efficiency":[194],"(i.e.":[195],"less":[196],"false":[197],"match":[198],"authentication).":[201],"Thus,":[202],"efficiently":[206],"detect":[207],"all":[208],"aforementioned":[211],"attributes,":[213],"developed":[215],"conventional":[217],"deep":[219],"learning":[220],"models.":[222],"models":[224,261],"trained":[226],"tested":[228],"diverse":[230],"challenging":[232],"datasets,":[235],"using":[236],"data":[237],"captured":[238],"from":[239],"traditional":[240],"cameras":[241],"devices,":[244],"when":[245],"operating":[246],"multiple":[248],"standoff":[249],"distances,":[250],"indoor":[253],"outdoor":[255],"conditions.":[256],"Our":[257],"proposed":[258],"attribute-specific":[259],"detection":[260],"robust,":[263],"yielding":[264],"up":[265],"100%":[267],"accuracy":[268],"(in":[269],"terms":[270],"F1":[272],"score)":[273],"depending":[274],"tested,":[278],"as":[279,281],"well":[280],"model":[283],"dataset(s)":[285],"for":[287],"training":[288],"testing.":[290]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}