{"id":"https://openalex.org/W2977772559","doi":"https://doi.org/10.1109/ijcnn.2019.8851861","title":"Deep Q-Learning for Illumination and Rotation Invariant Face Detection","display_name":"Deep Q-Learning for Illumination and Rotation Invariant Face Detection","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2977772559","doi":"https://doi.org/10.1109/ijcnn.2019.8851861","mag":"2977772559"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851861","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851861","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/A5061630027","display_name":"Ariel Ruiz-Garcia","orcid":"https://orcid.org/0000-0002-2066-9217"},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ariel Ruiz-Garcia","raw_affiliation_strings":["School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom"],"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom","institution_ids":["https://openalex.org/I73417466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076935774","display_name":"Vasile Palade","orcid":"https://orcid.org/0000-0002-6768-8394"},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Vasile Palade","raw_affiliation_strings":["School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom"],"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom","institution_ids":["https://openalex.org/I73417466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015102986","display_name":"Ibrahim Almakky","orcid":"https://orcid.org/0009-0008-8802-7107"},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ibrahim Almakky","raw_affiliation_strings":["School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom"],"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom","institution_ids":["https://openalex.org/I73417466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059233518","display_name":"Mark Elshaw","orcid":"https://orcid.org/0000-0003-3960-2650"},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mark Elshaw","raw_affiliation_strings":["School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom"],"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom","institution_ids":["https://openalex.org/I73417466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061630027"],"corresponding_institution_ids":["https://openalex.org/I73417466"],"apc_list":null,"apc_paid":null,"fwci":0.2024,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54276085,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"518","issue":null,"first_page":"1","last_page":"8"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9988999962806702,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9944999814033508,"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":0.7819758653640747},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.675613522529602},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6679396629333496},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6621752977371216},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.6517945528030396},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6119360327720642},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5785028338432312},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5756315588951111},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5260438919067383},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5214670896530151},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5201826095581055},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5163489580154419},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4708877205848694},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.42991548776626587},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.4223771393299103},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41240444779396057},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1862277090549469},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17602583765983582}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7819758653640747},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.675613522529602},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6679396629333496},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6621752977371216},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6517945528030396},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6119360327720642},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5785028338432312},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5756315588951111},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5260438919067383},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5214670896530151},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5201826095581055},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5163489580154419},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4708877205848694},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.42991548776626587},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4223771393299103},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41240444779396057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1862277090549469},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17602583765983582},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851861","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851861","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1757796397","https://openalex.org/W1977863971","https://openalex.org/W2017836770","https://openalex.org/W2046399019","https://openalex.org/W2047508432","https://openalex.org/W2100474751","https://openalex.org/W2103943262","https://openalex.org/W2106115875","https://openalex.org/W2121863487","https://openalex.org/W2123921160","https://openalex.org/W2145339207","https://openalex.org/W2162803672","https://openalex.org/W2296659146","https://openalex.org/W2737047298","https://openalex.org/W2768460137","https://openalex.org/W2776507577","https://openalex.org/W2896863246","https://openalex.org/W2900634895","https://openalex.org/W2964095005","https://openalex.org/W2964309795","https://openalex.org/W3097096317","https://openalex.org/W4214717370","https://openalex.org/W4298857966","https://openalex.org/W6637967152","https://openalex.org/W6662335928"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"The":[0,140],"domain":[1],"of":[2,21,152,162],"automatic":[3],"face":[4,39,70,86],"detection":[5,40,71],"is":[6,24],"a":[7,62,91,97,110,134,138],"challenging":[8],"problem":[9],"that":[10,128,156],"has":[11],"made":[12],"great":[13],"progress":[14,23],"in":[15,30,53,85,96],"the":[16,27,54,114,120],"last":[17],"two":[18],"decades.":[19],"Much":[20],"this":[22,58],"due":[25],"to":[26,49,123,132],"continuous":[28],"advancements":[29],"deep":[31,111],"learning":[32],"and":[33,82,154],"computer":[34],"vision.":[35],"Nonetheless,":[36],"contemporary":[37],"state-of-the-art":[38,144],"models":[41],"rely":[42],"on":[43,72,113,147],"exhaustive":[44],"search":[45],"or":[46],"are":[47],"unable":[48],"deal":[50],"with":[51,74,149,159],"changes":[52],"data":[55,73],"distribution.":[56],"In":[57],"work,":[59],"we":[60,79,89],"propose":[61],"novel":[63],"Deep":[64],"Reinforcement":[65],"Learning":[66],"(DRL)":[67],"approach":[68,142],"for":[69,102],"nonuniform":[75],"conditions.":[76],"More":[77],"specifically,":[78],"address":[80],"illumination":[81,103,115,153],"rotation":[83],"invariance":[84],"detection.":[87],"Firstly,":[88],"train":[90,109],"Stacked":[92],"Convolutional":[93],"Autoencoder":[94],"(SCAE)":[95],"greedy":[98],"layer-wise":[99],"unsupervised":[100],"fashion":[101],"invariant":[104,116],"feature":[105],"extraction.":[106],"We":[107],"then":[108],"Q-network":[112],"features":[117],"produced":[118],"by":[119],"SCAE":[121],"model,":[122],"learn":[124],"an":[125,130],"action-value":[126],"policy":[127],"allows":[129],"agent":[131],"place":[133],"bounding":[135],"box":[136],"around":[137],"face.":[139],"proposed":[141],"achieves":[143],"recognition":[145],"rates":[146],"images":[148,155],"varying":[150],"degrees":[151],"contain":[157],"faces":[158],"some":[160],"degree":[161],"rotation.":[163]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
