{"id":"https://openalex.org/W2057064510","doi":"https://doi.org/10.1145/2808492.2808570","title":"Robust gender classification on unconstrained face images","display_name":"Robust gender classification on unconstrained face images","publication_year":2015,"publication_date":"2015-08-19","ids":{"openalex":"https://openalex.org/W2057064510","doi":"https://doi.org/10.1145/2808492.2808570","mag":"2057064510"},"language":"en","primary_location":{"id":"doi:10.1145/2808492.2808570","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808492.2808570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Internet Multimedia Computing and Service","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/A5022675701","display_name":"Fudong Nian","orcid":"https://orcid.org/0000-0001-9604-7564"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fudong Nian","raw_affiliation_strings":["Anhui University, HeFei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University, HeFei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078572839","display_name":"Lanying Li","orcid":"https://orcid.org/0000-0001-9087-4833"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lanying Li","raw_affiliation_strings":["Anhui University, HeFei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University, HeFei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416750","display_name":"Teng Li","orcid":"https://orcid.org/0000-0003-0111-0108"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Teng Li","raw_affiliation_strings":["Anhui University, HeFei, China and Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University, HeFei, China and Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I143868143","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022636178","display_name":"Changsheng Xu","orcid":"https://orcid.org/0000-0001-8343-9665"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Xu","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5407,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.7425775,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9994999766349792,"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":0.9994999766349792,"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/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/T10828","display_name":"Biometric Identification and Security","score":0.9865999817848206,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8391363620758057},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.8100800514221191},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7715293169021606},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7477787733078003},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6153343915939331},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5539382100105286},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5217400789260864},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.5184823870658875},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5008335113525391},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4898035526275635},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4278397560119629},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.419063925743103},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4125669002532959},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13655120134353638}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8391363620758057},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.8100800514221191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7715293169021606},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7477787733078003},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6153343915939331},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5539382100105286},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5217400789260864},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.5184823870658875},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5008335113525391},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4898035526275635},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4278397560119629},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.419063925743103},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4125669002532959},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13655120134353638},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/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},{"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:10.1145/2808492.2808570","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808492.2808570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Internet Multimedia Computing and Service","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5"}],"awards":[{"id":"https://openalex.org/G5771837786","display_name":null,"funder_award_id":"61300056","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"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":13,"referenced_works":["https://openalex.org/W182571476","https://openalex.org/W1677182931","https://openalex.org/W1759745650","https://openalex.org/W1782590233","https://openalex.org/W1905153633","https://openalex.org/W1965804146","https://openalex.org/W1976948919","https://openalex.org/W1997011019","https://openalex.org/W2028337883","https://openalex.org/W2033940656","https://openalex.org/W2056865454","https://openalex.org/W2149494055","https://openalex.org/W2155893237"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2952813363","https://openalex.org/W4360783045"],"abstract_inverted_index":{"Robust":[0],"and":[1,54,101,147],"automatic":[2],"gender":[3,44],"classification":[4,45],"on":[5,46,51,68,135],"a":[6,63],"single":[7],"face":[8,48,90,99,109,115,128],"image":[9,91],"is":[10,104],"one":[11],"of":[12,27,32,42,65,84,88],"the":[13,30,40,71,85,89,136,144,150,156],"fundamental":[14],"artificial":[15],"intelligence":[16],"tasks.":[17],"And":[18],"it":[19,148],"has":[20,61,74],"become":[21],"relevant":[22],"to":[23,106],"an":[24,97],"increasing":[25],"amount":[26],"applications":[28],"alongside":[29],"rise":[31],"social":[33],"media.":[34],"In":[35],"this":[36,69],"paper":[37],"we":[38,112],"consider":[39],"problem":[41],"robust":[43],"unconstrained":[47,108,127,138],"images":[49,129],"based":[50],"weakly":[52],"calibration":[53,102],"deep":[55,114,118],"neural":[56,120],"network":[57],"methods.":[58],"While":[59],"there":[60],"been":[62],"lot":[64],"significant":[66],"researches":[67],"problem,":[70],"proposed":[72,105],"method":[73,103,134],"distinct":[75],"advantages":[76],"compared":[77],"with":[78],"other":[79],"approaches.":[80],"To":[81],"facilitate":[82],"tolerance":[83],"pose":[86],"variations":[87],"caused":[92],"by":[93],"different":[94],"shooting":[95],"angles,":[96],"efficient":[98],"detection":[100],"preprocess":[107],"images.":[110],"Furthermore,":[111],"extract":[113],"representations":[116],"using":[117],"convolutional":[119],"networks":[121],"(CNN)":[122],"which":[123],"could":[124],"handle":[125],"all":[126],"efficiently.":[130],"We":[131],"evaluate":[132],"our":[133],"real-life":[137],"faces":[139],"database-the":[140],"Labeled":[141],"Faces":[142],"in":[143,155],"Wild":[145],"(LFW)":[146],"outperforms":[149],"previous":[151],"best":[152],"results":[153],"reported":[154],"literature.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
