{"id":"https://openalex.org/W2897090561","doi":"https://doi.org/10.1109/ijcnn.2018.8489570","title":"Deep Modeling of Human Age Guesses for Apparent Age Estimation","display_name":"Deep Modeling of Human Age Guesses for Apparent Age Estimation","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2897090561","doi":"https://doi.org/10.1109/ijcnn.2018.8489570","mag":"2897090561"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2018.8489570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://digitalcommons.uri.edu/cs_facpubs/30","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108667633","display_name":"Jared Rondeau","orcid":null},"institutions":[{"id":"https://openalex.org/I17626003","display_name":"University of Rhode Island","ror":"https://ror.org/013ckk937","country_code":"US","type":"education","lineage":["https://openalex.org/I17626003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jared Rondeau","raw_affiliation_strings":["Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI","institution_ids":["https://openalex.org/I17626003"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046665875","display_name":"Marco \u00c1lvarez","orcid":"https://orcid.org/0000-0002-8528-5089"},"institutions":[{"id":"https://openalex.org/I17626003","display_name":"University of Rhode Island","ror":"https://ror.org/013ckk937","country_code":"US","type":"education","lineage":["https://openalex.org/I17626003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marco Alvarez","raw_affiliation_strings":["Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI","institution_ids":["https://openalex.org/I17626003"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17626003"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"01","last_page":"08"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9635999798774719,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9620000123977661,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7372981905937195},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7120067477226257},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6955757141113281},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.6659848690032959},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6399347186088562},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.5894885659217834},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5768972039222717},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5590737462043762},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5538589954376221},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5282952785491943},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5263679623603821},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5009245872497559},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4108603894710541},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.3260909914970398},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.26183363795280457},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21181538701057434}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7372981905937195},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7120067477226257},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955757141113281},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.6659848690032959},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6399347186088562},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.5894885659217834},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5768972039222717},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5590737462043762},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5538589954376221},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5282952785491943},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5263679623603821},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5009245872497559},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4108603894710541},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3260909914970398},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26183363795280457},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21181538701057434},{"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2018.8489570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:digitalcommons.uri.edu:cs_facpubs-1029","is_oa":true,"landing_page_url":"https://digitalcommons.uri.edu/cs_facpubs/30","pdf_url":null,"source":{"id":"https://openalex.org/S2764761010","display_name":"Journal of Media Literacy Education","issn_l":"2167-8715","issn":["2167-8715"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310316378","host_organization_name":"National Association for Media Literacy Education","host_organization_lineage":["https://openalex.org/P4310316378"],"host_organization_lineage_names":["National Association for Media Literacy Education"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Science and Statistics Faculty Publications","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:digitalcommons.uri.edu:cs_facpubs-1029","is_oa":true,"landing_page_url":"https://digitalcommons.uri.edu/cs_facpubs/30","pdf_url":null,"source":{"id":"https://openalex.org/S2764761010","display_name":"Journal of Media Literacy Education","issn_l":"2167-8715","issn":["2167-8715"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310316378","host_organization_name":"National Association for Media Literacy Education","host_organization_lineage":["https://openalex.org/P4310316378"],"host_organization_lineage_names":["National Association for Media Literacy Education"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Science and Statistics Faculty Publications","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2036565334","https://openalex.org/W2066454034","https://openalex.org/W2096175520","https://openalex.org/W2105026179","https://openalex.org/W2129905273","https://openalex.org/W2141461916","https://openalex.org/W2249960609","https://openalex.org/W2253728219","https://openalex.org/W2269758193","https://openalex.org/W2330485005","https://openalex.org/W2440214111","https://openalex.org/W2442264559","https://openalex.org/W2510725918","https://openalex.org/W2528176169","https://openalex.org/W2553156677","https://openalex.org/W2572206410","https://openalex.org/W2593927017","https://openalex.org/W2618390276","https://openalex.org/W2725329413","https://openalex.org/W2963446712","https://openalex.org/W2963878055","https://openalex.org/W3105616927","https://openalex.org/W4233014035","https://openalex.org/W6674650171","https://openalex.org/W6694232893","https://openalex.org/W6725236325","https://openalex.org/W6732436211","https://openalex.org/W6734338310"],"related_works":["https://openalex.org/W3000866861","https://openalex.org/W3156786002","https://openalex.org/W4381487685","https://openalex.org/W2738221750","https://openalex.org/W3021430260","https://openalex.org/W564581980","https://openalex.org/W2337926734","https://openalex.org/W4366224123","https://openalex.org/W4320802194","https://openalex.org/W2995227436"],"abstract_inverted_index":{"In":[0,52],"this":[1],"paper":[2],"we":[3,55],"propose":[4],"a":[5,22,35,102],"unique":[6],"deep":[7],"learning":[8],"formulation":[9],"of":[10,37,41,106],"the":[11,17,42,62,75,98,112],"apparent":[12,94],"age":[13,95],"estimation":[14,96],"problem,":[15],"using":[16,111],"APPA-Real":[18,20,99],"dataset.":[19,114],"is":[21,32],"dataset":[23,100],"containing":[24],"7,":[25],"591":[26],"face":[27],"images,":[28],"where":[29],"each":[30],"image":[31],"labeled":[33],"by":[34],"set":[36],"approximately":[38],"38":[39],"guesses":[40,46],"facial":[43],"age.":[44],"All":[45],"are":[47],"collected":[48],"from":[49,61],"human":[50,63],"labelers.":[51],"our":[53],"approach,":[54],"first":[56],"generate":[57],"per-image":[58],"label":[59,68],"distributions":[60,69],"guesses,":[64],"and":[65,74],"then":[66],"learn":[67],"with":[70,85,101],"convolutional":[71],"neural":[72],"networks":[73],"KL-divergence":[76],"loss":[77],"function.":[78],"We":[79,89],"provide":[80],"comparisons":[81],"to":[82],"models":[83],"trained":[84],"other":[86,109],"objective":[87],"functions.":[88],"achieve":[90],"state-of-the-art":[91],"results":[92],"for":[93],"on":[97],"mean":[103],"absolute":[104],"error":[105],"3.688,":[107],"outperforming":[108],"methods":[110],"same":[113]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}