{"id":"https://openalex.org/W2971724078","doi":"https://doi.org/10.1145/3351108.3351123","title":"Age and Gender Estimation using Optimised Deep Networks","display_name":"Age and Gender Estimation using Optimised Deep Networks","publication_year":2019,"publication_date":"2019-09-03","ids":{"openalex":"https://openalex.org/W2971724078","doi":"https://doi.org/10.1145/3351108.3351123","mag":"2971724078"},"language":"en","primary_location":{"id":"doi:10.1145/3351108.3351123","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3351108.3351123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019","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/A5023490989","display_name":"Wade Downton","orcid":null},"institutions":[{"id":"https://openalex.org/I192619145","display_name":"University of the Witwatersrand","ror":"https://ror.org/03rp50x72","country_code":"ZA","type":"education","lineage":["https://openalex.org/I192619145"]}],"countries":["ZA"],"is_corresponding":true,"raw_author_name":"Wade Downton","raw_affiliation_strings":["School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa","institution_ids":["https://openalex.org/I192619145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081793269","display_name":"Hima Vadapalli","orcid":"https://orcid.org/0000-0001-9040-3601"},"institutions":[{"id":"https://openalex.org/I192619145","display_name":"University of the Witwatersrand","ror":"https://ror.org/03rp50x72","country_code":"ZA","type":"education","lineage":["https://openalex.org/I192619145"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Hima Vadapalli","raw_affiliation_strings":["School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa","institution_ids":["https://openalex.org/I192619145"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023490989"],"corresponding_institution_ids":["https://openalex.org/I192619145"],"apc_list":null,"apc_paid":null,"fwci":0.1012,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43734526,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9962000250816345,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958000183105469,"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":0.7490158081054688},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.747199296951294},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7324440479278564},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5712063312530518},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5613172054290771},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5510280728340149},{"id":"https://openalex.org/keywords/activation-function","display_name":"Activation function","score":0.5103098750114441},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5033420920372009},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.47755512595176697},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4273570477962494},{"id":"https://openalex.org/keywords/hyperbolic-function","display_name":"Hyperbolic function","score":0.4142988920211792},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41200077533721924},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38645702600479126},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.34257927536964417},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3420976400375366},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17207005620002747},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10378891229629517}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7490158081054688},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.747199296951294},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7324440479278564},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5712063312530518},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5613172054290771},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5510280728340149},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.5103098750114441},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5033420920372009},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.47755512595176697},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4273570477962494},{"id":"https://openalex.org/C92047909","wikidata":"https://www.wikidata.org/wiki/Q204034","display_name":"Hyperbolic function","level":2,"score":0.4142988920211792},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41200077533721924},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38645702600479126},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.34257927536964417},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3420976400375366},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17207005620002747},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10378891229629517},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3351108.3351123","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3351108.3351123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1849007038","https://openalex.org/W1905153633","https://openalex.org/W1965804146","https://openalex.org/W2159386181","https://openalex.org/W2168893862","https://openalex.org/W2176412452","https://openalex.org/W2244579295","https://openalex.org/W2249451056","https://openalex.org/W2279639021","https://openalex.org/W2325939864","https://openalex.org/W2414236216","https://openalex.org/W2498789492","https://openalex.org/W2587795518","https://openalex.org/W2765833400","https://openalex.org/W2767286248","https://openalex.org/W2786164505","https://openalex.org/W2951635495","https://openalex.org/W2963266717","https://openalex.org/W3214102110","https://openalex.org/W4238416801"],"related_works":["https://openalex.org/W3024877706","https://openalex.org/W3022392884","https://openalex.org/W4210854505","https://openalex.org/W3012219884","https://openalex.org/W4295036712","https://openalex.org/W4375958661","https://openalex.org/W4385451479","https://openalex.org/W4211198594","https://openalex.org/W2811324119","https://openalex.org/W3187603754"],"abstract_inverted_index":{"Age":[0],"and":[1,55,58,60,65,82,88,112,126,139,188],"gender":[2,137,187],"estimation":[3,34,170,197],"plays":[4],"a":[5,27,40,75,132,165],"fundamental":[6],"role":[7],"in":[8,131,142,150],"intelligent":[9],"applications":[10],"such":[11,98],"as":[12,99],"access":[13],"control,":[14],"marketing":[15],"intelligence,":[16],"human-computer":[17],"interaction":[18],"etc.":[19],"The":[20,161],"advent":[21],"of":[22,33,42,51,74,86,93,123,146,177,186,194],"deep":[23,77],"architectures":[24],"have":[25],"paved":[26],"way":[28],"to":[29,163,173],"improve":[30],"the":[31,49,121,153,174,190,195],"performance":[32],"models,":[35],"however,":[36,152],"there":[37],"is":[38,171],"still":[39],"lack":[41],"optimized":[43],"architectures.":[44],"This":[45,69],"paper":[46,70],"focuses":[47],"on":[48,63,80],"use":[50,73,122],"convolutional":[52,125],"neural":[53],"networks,":[54],"parameter":[56],"modeling":[57],"optimization,":[59],"their":[61],"effect":[62],"accuracy":[64],"loss":[66,92],"term":[67],"convergence.":[68],"first":[71],"makes":[72],"generalized":[76],"architecture":[78,135,167],"based":[79],"literature":[81],"looks":[83],"at":[84],"ways":[85],"optimizing":[87],"reducing":[89],"complexity":[90],"without":[91],"accuracy.":[94],"Different":[95],"activation":[96],"functions":[97],"rectified":[100],"linear":[101,104,107],"unit":[102,108],"(ReLU),":[103],"function,":[105],"exponential":[106],"(ELU),":[109],"hyperbolic":[110],"tangent":[111],"Googles'":[113],"proposed":[114],"Swish":[115],"function":[116],"were":[117,141],"tested":[118],"along":[119],"with":[120,144,182],"additional":[124],"fully-connected":[127],"layers.":[128],"Experiments":[129],"resulted":[130],"less":[133],"complex":[134,175],"for":[136,158,168],"classification":[138,192],"results":[140],"line":[143],"that":[145,179,185],"benchmark":[147],"accuracies":[148],"found":[149],"literature,":[151],"same":[154],"couldn't":[155],"be":[156],"achieved":[157],"age":[159,169,183,196],"estimation.":[160],"inability":[162],"find":[164],"simpler":[166],"attributed":[172],"nature":[176,193],"features":[178],"are":[180],"associated":[181],"than":[184],"also":[189],"multi-class":[191],"problem.":[198]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
