{"id":"https://openalex.org/W2978002283","doi":"https://doi.org/10.1109/ijcnn.2019.8852273","title":"Comparative study between Deep Face, Autoencoder and Traditional Machine Learning Techniques aiming at Biometric Facial Recognition","display_name":"Comparative study between Deep Face, Autoencoder and Traditional Machine Learning Techniques aiming at Biometric Facial Recognition","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978002283","doi":"https://doi.org/10.1109/ijcnn.2019.8852273","mag":"2978002283"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5091206917","display_name":"Jonnathann Silva Finizola","orcid":null},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Jonnathann S. Finizola","raw_affiliation_strings":["University of Sao Paulo, Sao Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"University of Sao Paulo, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021633221","display_name":"Jonas M. Targino","orcid":null},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jonas M. Targino","raw_affiliation_strings":["University of Sao Paulo, Sao Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"University of Sao Paulo, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015203782","display_name":"Felipe Gustavo Silva Teodoro","orcid":null},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Felipe G.S. Teodoro","raw_affiliation_strings":["University of Sao Paulo, Sao Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"University of Sao Paulo, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030763025","display_name":"Clodoaldo A. M. Lima","orcid":"https://orcid.org/0000-0003-3381-5348"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Clodoaldo A.M Lima","raw_affiliation_strings":["University of Sao Paulo, Sao Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"University of Sao Paulo, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I17974374"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091206917"],"corresponding_institution_ids":["https://openalex.org/I17974374"],"apc_list":null,"apc_paid":null,"fwci":0.9951,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.76543513,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9968000054359436,"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"}},"topics":[{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9968000054359436,"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/T11448","display_name":"Face recognition and analysis","score":0.9965999722480774,"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":0.9930999875068665,"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/autoencoder","display_name":"Autoencoder","score":0.848395824432373},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.8174893856048584},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7829384207725525},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.774052619934082},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.773166298866272},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6284915804862976},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6125717759132385},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5512040853500366},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5446531176567078},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4895547330379486},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4489801824092865},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4143255054950714},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32433342933654785}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.848395824432373},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.8174893856048584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7829384207725525},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.774052619934082},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.773166298866272},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6284915804862976},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6125717759132385},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5512040853500366},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5446531176567078},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4895547330379486},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4489801824092865},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4143255054950714},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32433342933654785},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W191940071","https://openalex.org/W1512748702","https://openalex.org/W1663792126","https://openalex.org/W1999533590","https://openalex.org/W2047822984","https://openalex.org/W2096987757","https://openalex.org/W2097290407","https://openalex.org/W2106115875","https://openalex.org/W2109173556","https://openalex.org/W2111072639","https://openalex.org/W2132984323","https://openalex.org/W2137857332","https://openalex.org/W2145287260","https://openalex.org/W2153635508","https://openalex.org/W2158120166","https://openalex.org/W2178615544","https://openalex.org/W2209882149","https://openalex.org/W2292645027","https://openalex.org/W2348012741","https://openalex.org/W2401188729","https://openalex.org/W2513847451","https://openalex.org/W2549555466","https://openalex.org/W2573123015","https://openalex.org/W2627083872","https://openalex.org/W2994340921","https://openalex.org/W3097096317","https://openalex.org/W4248916828","https://openalex.org/W6630661224","https://openalex.org/W6635552349","https://openalex.org/W6656661550","https://openalex.org/W6685730785"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2145836866","https://openalex.org/W2803255133","https://openalex.org/W2985118265"],"abstract_inverted_index":{"Biometric":[0],"technology":[1],"is":[2,18,23,37,115,147],"increasingly":[3],"present":[4],"in":[5,10,26,109,136],"our":[6],"daily":[7],"lives":[8],"whether":[9],"mobile":[11],"devices":[12],"or":[13,50],"commercial":[14],"sectors":[15],"because":[16],"it":[17],"an":[19],"approach":[20],"where":[21],"there":[22,114],"great":[24],"difficulty":[25],"being":[27,56],"circumvented,":[28],"unlike":[29],"traditional":[30,96,127,154],"models":[31,155],"of":[32,53,76,84,89,132,144,156],"security":[33],"and":[34,47,57,78,159,167],"identification.":[35],"Biometrics":[36],"the":[38,54,58,63,82,110,142],"means":[39],"by":[40],"which":[41],"these":[42],"technologies":[43],"can":[44,61,73,122],"identify":[45],"individuals":[46],"uses":[48],"physical":[49,59],"behavioral":[51,71],"characteristics":[52,60],"human":[55],"be:":[62,74],"iris,":[64],"face,":[65],"palm,":[66],"fingerprint,":[67],"among":[68],"others.":[69],"The":[70],"ones":[72],"way":[75],"walking":[77],"typing":[79],"dynamics.":[80],"With":[81],"emergence":[83],"Deep":[85,120,160],"Learning,":[86],"a":[87,150],"number":[88],"problems":[90],"that":[91,119],"were":[92],"once":[93],"solved":[94],"with":[95,105,129],"machine":[97,157],"learning":[98,158],"models,":[99,128],"have":[100],"come":[101],"to":[102,148],"better":[103,124],"results":[104,125],"this":[106,145],"approach,":[107],"but":[108],"face":[111],"recognition":[112],"environment":[113],"still":[116],"no":[117],"evidence":[118],"Learning":[121,161],"achieve":[123],"than":[126],"different":[130,137],"extractors":[131],"characteristics,":[133],"when":[134],"applied":[135],"databases":[138],"facial":[139,170],"data.":[140],"Therefore,":[141],"objective":[143],"work":[146],"perform":[149],"comparative":[151],"study":[152],"between":[153],"focusing":[162],"on":[163],"Convolutional":[164],"Neural":[165],"Networks":[166],"Autoencoders":[168],"for":[169],"recognition.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
