{"id":"https://openalex.org/W2790217705","doi":"https://doi.org/10.1109/icip.2017.8296450","title":"Deep embedding network for robust age estimation","display_name":"Deep embedding network for robust age estimation","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2790217705","doi":"https://doi.org/10.1109/icip.2017.8296450","mag":"2790217705"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5089762563","display_name":"Yating He","orcid":null},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yating He","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076579785","display_name":"Min Huang","orcid":"https://orcid.org/0000-0001-7141-7434"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Huang","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113720333","display_name":"Qinghai Miao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghai Miao","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085707125","display_name":"Haiyun Guo","orcid":"https://orcid.org/0000-0001-9241-6211"},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyun Guo","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058420913","display_name":"Jinqiao Wang","orcid":"https://orcid.org/0000-0002-9118-2780"},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinqiao Wang","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China","University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2388,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64236125,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"17","issue":null,"first_page":"1092","last_page":"1096"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9872999787330627,"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":0.9617999792098999,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.8189377784729004},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.74997878074646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6814831495285034},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6516427993774414},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5828126668930054},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5387829542160034},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5141416192054749},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5114209055900574},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4709300398826599},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4559739828109741},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.43207019567489624},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3864724040031433},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3214806020259857},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20800086855888367}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.8189377784729004},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.74997878074646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6814831495285034},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6516427993774414},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5828126668930054},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5387829542160034},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5141416192054749},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5114209055900574},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4709300398826599},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4559739828109741},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.43207019567489624},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3864724040031433},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3214806020259857},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20800086855888367},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W219040644","https://openalex.org/W1488606709","https://openalex.org/W1686810756","https://openalex.org/W1712881228","https://openalex.org/W1849007038","https://openalex.org/W1972960842","https://openalex.org/W2009088607","https://openalex.org/W2032454342","https://openalex.org/W2046968680","https://openalex.org/W2056783896","https://openalex.org/W2075875861","https://openalex.org/W2098121127","https://openalex.org/W2103077782","https://openalex.org/W2106488920","https://openalex.org/W2112796928","https://openalex.org/W2132852291","https://openalex.org/W2147278565","https://openalex.org/W2151386286","https://openalex.org/W2164715565","https://openalex.org/W2239239723","https://openalex.org/W2440214111","https://openalex.org/W6638943231","https://openalex.org/W6678300183","https://openalex.org/W6679777679"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W51364034","https://openalex.org/W2141938446","https://openalex.org/W2898073868","https://openalex.org/W4284663758"],"abstract_inverted_index":{"Estimating":[0],"age":[1,22,48,82,108],"through":[2],"a":[3,8,62],"single":[4],"facial":[5,17,70],"image":[6],"is":[7],"classic":[9],"and":[10,56,85,103,138],"challenging":[11],"topic":[12],"in":[13],"computer":[14],"vision.":[15],"Since":[16],"images":[18,71],"of":[19,79,115,143],"the":[20,68,80,94,105,113,116,127,141,148],"same":[21,81],"vary":[23],"considerably,":[24],"while":[25],"those":[26,86],"from":[27,87],"different":[28,88],"ages":[29,89],"may":[30],"look":[31],"very":[32],"similar.":[33],"To":[34],"address":[35],"these":[36],"problems,":[37],"we":[38,51,118],"propose":[39],"an":[40,73,120],"end-to-end":[41],"deep":[42,63,95],"embedding":[43,64,74,96],"neural":[44],"network":[45,97],"for":[46,107],"robust":[47],"estimation.":[49,109],"Specifically,":[50],"jointly":[52],"use":[53],"classification":[54],"loss":[55,59,129],"triplet-based":[57],"ranking":[58],"to":[60,111,147],"train":[61],"network,":[65,117],"which":[66],"maps":[67],"input":[69],"into":[72],"metric":[75],"space":[76],"where":[77],"features":[78,102],"are":[83,90],"compact":[84],"pushed":[91],"away.":[92],"Thus":[93],"can":[98],"learn":[99],"more":[100],"discriminative":[101],"improves":[104],"performance":[106],"Additionally,":[110],"accelerate":[112],"convergence":[114],"adopt":[119],"online":[121],"hard":[122],"negative":[123],"mining":[124],"strategy":[125],"during":[126],"triplet":[128],"computation.":[130],"Experimental":[131],"results":[132],"on":[133],"public":[134],"datasets":[135],"MORPH":[136],"II":[137],"FG-NET":[139],"show":[140],"superiority":[142],"our":[144],"approach":[145],"compared":[146],"state-of-the-art.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
