{"id":"https://openalex.org/W4415974167","doi":"https://doi.org/10.1016/j.procs.2025.09.562","title":"A New Attention-based Architecture for Robust Face-Age Recognition","display_name":"A New Attention-based Architecture for Robust Face-Age Recognition","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415974167","doi":"https://doi.org/10.1016/j.procs.2025.09.562"},"language":"en","primary_location":{"id":"doi:10.1016/j.procs.2025.09.562","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2025.09.562","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1016/j.procs.2025.09.562","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066061742","display_name":"Amal Abbes","orcid":"https://orcid.org/0000-0002-0841-3614"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Amal Abbes","raw_affiliation_strings":["Multimedia InfoRmation systems and Advanced Computing Laboratory, MIRACL, University of Sfax, Tunisia"],"affiliations":[{"raw_affiliation_string":"Multimedia InfoRmation systems and Advanced Computing Laboratory, MIRACL, University of Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002474870","display_name":"Yassine Ben Ayed","orcid":"https://orcid.org/0000-0002-3676-3670"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Yassine Ben Ayed","raw_affiliation_strings":["Multimedia InfoRmation systems and Advanced Computing Laboratory, MIRACL, University of Sfax, Tunisia"],"affiliations":[{"raw_affiliation_string":"Multimedia InfoRmation systems and Advanced Computing Laboratory, MIRACL, University of Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5002474870","https://openalex.org/A5066061742"],"corresponding_institution_ids":["https://openalex.org/I142899784"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35457227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"270","issue":null,"first_page":"4373","last_page":"4381"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9879999756813049,"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":0.9879999756813049,"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/T11322","display_name":"Facial Rejuvenation and Surgery Techniques","score":0.002400000113993883,"subfield":{"id":"https://openalex.org/subfields/2708","display_name":"Dermatology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.00139999995008111,"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/facial-recognition-system","display_name":"Facial recognition system","score":0.6686999797821045},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5515000224113464},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5490000247955322},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.544700026512146},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4925999939441681},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4388999938964844},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4327999949455261},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.39340001344680786},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.38830000162124634}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8705000281333923},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6686999797821045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.654699981212616},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5515000224113464},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5490000247955322},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.544700026512146},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4925999939441681},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4747999906539917},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4388999938964844},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4327999949455261},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.39340001344680786},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.38830000162124634},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.3456999957561493},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.32030001282691956},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C191070858","wikidata":"https://www.wikidata.org/wiki/Q5428343","display_name":"Face Recognition Grand Challenge","level":5,"score":0.3091000020503998},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2833999991416931},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2685999870300293},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C39896193","wikidata":"https://www.wikidata.org/wiki/Q380344","display_name":"Descriptive statistics","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.procs.2025.09.562","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2025.09.562","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.procs.2025.09.562","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2025.09.562","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W194347024","https://openalex.org/W574081047","https://openalex.org/W1552621978","https://openalex.org/W1905153633","https://openalex.org/W1965804146","https://openalex.org/W2026631319","https://openalex.org/W2033173798","https://openalex.org/W2039140324","https://openalex.org/W2096733369","https://openalex.org/W2149298154","https://openalex.org/W2548780814","https://openalex.org/W2559806528","https://openalex.org/W2595730420","https://openalex.org/W2736641890","https://openalex.org/W3042534232","https://openalex.org/W3165842532","https://openalex.org/W4213019189","https://openalex.org/W4293065409","https://openalex.org/W4383560118","https://openalex.org/W4386188499","https://openalex.org/W4390873137","https://openalex.org/W4391259676","https://openalex.org/W4392506559","https://openalex.org/W4399488221","https://openalex.org/W4402603550"],"related_works":[],"abstract_inverted_index":{"Face":[0],"age":[1,31,52,62,76,94,114,145],"recognition":[2,77,183],"task":[3],"has":[4],"become":[5],"essential":[6],"in":[7,20,67,153],"several":[8],"applications":[9],"like":[10],"minors":[11],"security":[12],"and":[13,26,40,49,59,82,100],"marketing.":[14],"However,":[15],"despite":[16],"the":[17,37,79,93,104,112,127,132,143,158,173],"recent":[18,176],"advances":[19],"deep":[21],"learning":[22],"algorithms,":[23],"developing":[24],"accurate":[25],"efficient":[27],"architecture":[28,81],"for":[29,110,156],"face":[30,51,61,75,113],"classification":[32],"remains":[33],"difficult":[34],"due":[35],"to":[36,73,125,140],"unconstrained":[38],"environment":[39],"variation":[41],"on":[42],"aging":[43],"effect.":[44],"Requiring":[45,55],"both":[46,56],"a":[47,57,70,118],"distinctive":[48,58],"descriptive":[50,60,129],"representation":[53,63,95],"model.":[54,102],"models.":[64],"We":[65],"introduce,":[66],"this":[68],"paper,":[69],"three-stage":[71],"system":[72,89],"enhance":[74],"using":[78,96],"transformer":[80],"pre-trained":[83],"Convolutional":[84],"Neural":[85],"Networks":[86],"(CNN).":[87],"The":[88,147,161],"begins":[90],"with":[91,180],"extracting":[92],"Vision":[97],"Transforms":[98],"(ViT)":[99],"FaceNet":[101],"Subsequently,":[103],"Pearson":[105],"correlation":[106],"coefficient":[107],"is":[108,123,138],"considered":[109,152],"selecting":[111],"pertinent":[115],"features.":[116],"Hence,":[117],"Multi-Head":[119],"Attention":[120],"(MHA)":[121],"block":[122],"used":[124],"extract":[126],"final":[128],"representation.":[130],"Finally,":[131],"Support":[133],"Vector":[134],"Machine":[135],"Classifier":[136],"(SVM)":[137],"trained":[139],"distinguish":[141],"between":[142],"different":[144],"classes.":[146],"challenging":[148],"FG-NET":[149],"dataset":[150],"was":[151],"our":[154,168],"work":[155,179],"evaluating":[157],"proposed":[159],"architecture.":[160],"conducted":[162],"experimental":[163],"study":[164],"shows":[165],"evidence":[166],"that":[167],"approach":[169],"ranks":[170],"top":[171],"of":[172,175],"list":[174],"potential":[177],"published":[178],"an":[181],"63%":[182],"rate.":[184]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-06T00:00:00"}
