{"id":"https://openalex.org/W3006399382","doi":"https://doi.org/10.1109/icce-tw46550.2019.8991688","title":"Age Estimation via Modern Convolutional Neural Networks","display_name":"Age Estimation via Modern Convolutional Neural Networks","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W3006399382","doi":"https://doi.org/10.1109/icce-tw46550.2019.8991688","mag":"3006399382"},"language":"en","primary_location":{"id":"doi:10.1109/icce-tw46550.2019.8991688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-tw46550.2019.8991688","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW)","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/A5036481579","display_name":"Kuan-Hsien Liu","orcid":"https://orcid.org/0000-0002-1411-2113"},"institutions":[{"id":"https://openalex.org/I131948415","display_name":"National Taichung University of Science and Technology","ror":"https://ror.org/05bgcav40","country_code":"TW","type":"education","lineage":["https://openalex.org/I131948415"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Kuan-Hsien Liu","raw_affiliation_strings":["National Taichung University of Science and Technology, Taichung"],"affiliations":[{"raw_affiliation_string":"National Taichung University of Science and Technology, Taichung","institution_ids":["https://openalex.org/I131948415"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062752232","display_name":"Chun-Te Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I131948415","display_name":"National Taichung University of Science and Technology","ror":"https://ror.org/05bgcav40","country_code":"TW","type":"education","lineage":["https://openalex.org/I131948415"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chun-Te Chang","raw_affiliation_strings":["National Taichung University of Science and Technology, Taichung"],"affiliations":[{"raw_affiliation_string":"National Taichung University of Science and Technology, Taichung","institution_ids":["https://openalex.org/I131948415"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023526360","display_name":"Tsung-Jung Liu","orcid":"https://orcid.org/0000-0003-4296-0942"},"institutions":[{"id":"https://openalex.org/I162838928","display_name":"National Chung Hsing University","ror":"https://ror.org/05vn3ca78","country_code":"TW","type":"education","lineage":["https://openalex.org/I162838928"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tsung-Jung Liu","raw_affiliation_strings":["National Chung Hsing University, Taichung"],"affiliations":[{"raw_affiliation_string":"National Chung Hsing University, Taichung","institution_ids":["https://openalex.org/I162838928"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036481579"],"corresponding_institution_ids":["https://openalex.org/I131948415"],"apc_list":null,"apc_paid":null,"fwci":0.3037,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62531747,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"10","issue":null,"first_page":"1","last_page":"2"},"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":0.9412999749183655,"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":0.9408000111579895,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8457894921302795},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.8083835244178772},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7336291074752808},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6885103583335876},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6271344423294067},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5819827914237976},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5214080810546875},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49303218722343445},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4769146144390106},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47482308745384216},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.462038516998291},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45593589544296265},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.41222071647644043},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38271310925483704}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8457894921302795},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.8083835244178772},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7336291074752808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6885103583335876},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6271344423294067},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5819827914237976},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5214080810546875},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49303218722343445},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4769146144390106},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47482308745384216},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.462038516998291},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45593589544296265},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.41222071647644043},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38271310925483704},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/icce-tw46550.2019.8991688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-tw46550.2019.8991688","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1567822572","https://openalex.org/W1686810756","https://openalex.org/W1849007038","https://openalex.org/W2066454034","https://openalex.org/W2097117768","https://openalex.org/W2118664399","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2510725918","https://openalex.org/W2517279376","https://openalex.org/W2531409750","https://openalex.org/W2535798196","https://openalex.org/W2725329413","https://openalex.org/W2731793484","https://openalex.org/W2798868324","https://openalex.org/W2805737268","https://openalex.org/W2807904173","https://openalex.org/W2897090561","https://openalex.org/W2912164984","https://openalex.org/W6637373629","https://openalex.org/W6677842256","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1999699871","https://openalex.org/W4225124612","https://openalex.org/W2043806667","https://openalex.org/W2021633306","https://openalex.org/W2006801911","https://openalex.org/W2033669961","https://openalex.org/W2971899271","https://openalex.org/W1972167985","https://openalex.org/W2350644419","https://openalex.org/W3165517033"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"apply":[4],"Xception":[5],"deep":[6],"convolutional":[7],"neural":[8],"network":[9],"for":[10],"age":[11,21],"estimation":[12],"on":[13,50,69],"facial":[14],"images.":[15],"We":[16,57],"adopt":[17],"Label":[18],"Distribution":[19],"Learning":[20],"encoding,":[22],"KLD":[23],"loss":[24],"function,":[25],"and":[26,66,72],"dropout":[27],"techniques":[28],"at":[29],"fully":[30],"connected":[31],"layers.":[32],"With":[33],"IMDB-WIKI":[34],"as":[35,43],"pre-training":[36],"dataset,":[37,45],"APPA-REAL":[38],"training":[39],"set":[40],"is":[41,53],"used":[42],"finetune":[44],"the":[46,54,59],"final":[47],"expected":[48],"value":[49],"model":[51],"output":[52],"estimated":[55],"age.":[56],"achieve":[58],"state-of-the-art":[60],"results":[61],"of":[62],"MAE":[63],"3.635,":[64],"2.78,":[65],"3.09":[67],"years":[68],"APPA-REAL,":[70],"FG-NET,":[71],"MORPH-II":[73],"test":[74],"sets,":[75],"respectively.":[76]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}