{"id":"https://openalex.org/W4327773141","doi":"https://doi.org/10.1109/sds57574.2022.10062889","title":"Multi-Task Deep Learning for Multimodal Biometric Recognition","display_name":"Multi-Task Deep Learning for Multimodal Biometric Recognition","publication_year":2022,"publication_date":"2022-12-12","ids":{"openalex":"https://openalex.org/W4327773141","doi":"https://doi.org/10.1109/sds57574.2022.10062889"},"language":"en","primary_location":{"id":"doi:10.1109/sds57574.2022.10062889","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sds57574.2022.10062889","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 Ninth International Conference on Software Defined Systems (SDS)","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/A5080938200","display_name":"Said Si Kaddour","orcid":null},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]},{"id":"https://openalex.org/I48825208","display_name":"Universit\u00e9 Paris 8","ror":"https://ror.org/04wez5e68","country_code":"FR","type":"education","lineage":["https://openalex.org/I48825208"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Said Si Kaddour","raw_affiliation_strings":["University of Paris 8,LIASD research Lab.,France","LIASD research Lab., University of Paris 8, France"],"affiliations":[{"raw_affiliation_string":"University of Paris 8,LIASD research Lab.,France","institution_ids":["https://openalex.org/I204730241","https://openalex.org/I48825208"]},{"raw_affiliation_string":"LIASD research Lab., University of Paris 8, France","institution_ids":["https://openalex.org/I204730241","https://openalex.org/I48825208"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074810075","display_name":"Larbi Boubchir","orcid":"https://orcid.org/0000-0002-5668-6801"},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]},{"id":"https://openalex.org/I48825208","display_name":"Universit\u00e9 Paris 8","ror":"https://ror.org/04wez5e68","country_code":"FR","type":"education","lineage":["https://openalex.org/I48825208"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Larbi Boubchir","raw_affiliation_strings":["University of Paris 8,LIASD research Lab.,France","LIASD research Lab., University of Paris 8, France"],"affiliations":[{"raw_affiliation_string":"University of Paris 8,LIASD research Lab.,France","institution_ids":["https://openalex.org/I204730241","https://openalex.org/I48825208"]},{"raw_affiliation_string":"LIASD research Lab., University of Paris 8, France","institution_ids":["https://openalex.org/I204730241","https://openalex.org/I48825208"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044161230","display_name":"Boubaker Da\u00e2chi","orcid":"https://orcid.org/0000-0002-8910-517X"},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]},{"id":"https://openalex.org/I48825208","display_name":"Universit\u00e9 Paris 8","ror":"https://ror.org/04wez5e68","country_code":"FR","type":"education","lineage":["https://openalex.org/I48825208"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Boubaker Daachi","raw_affiliation_strings":["University of Paris 8,LIASD research Lab.,France","LIASD research Lab., University of Paris 8, France"],"affiliations":[{"raw_affiliation_string":"University of Paris 8,LIASD research Lab.,France","institution_ids":["https://openalex.org/I204730241","https://openalex.org/I48825208"]},{"raw_affiliation_string":"LIASD research Lab., University of Paris 8, France","institution_ids":["https://openalex.org/I204730241","https://openalex.org/I48825208"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080938200"],"corresponding_institution_ids":["https://openalex.org/I204730241","https://openalex.org/I48825208"],"apc_list":null,"apc_paid":null,"fwci":0.2975,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53952469,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10828","display_name":"Biometric Identification and Security","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11448","display_name":"Face recognition and analysis","score":0.9958000183105469,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9761000275611877,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.9264132380485535},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7268292903900146},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6587744951248169},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6445802450180054},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.6266747713088989},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6020480990409851},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5763770937919617},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5483421087265015},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4898676574230194},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3784465193748474},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.33939430117607117},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1501500904560089}],"concepts":[{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.9264132380485535},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7268292903900146},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6587744951248169},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6445802450180054},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.6266747713088989},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6020480990409851},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5763770937919617},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5483421087265015},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4898676574230194},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3784465193748474},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33939430117607117},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1501500904560089},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sds57574.2022.10062889","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sds57574.2022.10062889","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 Ninth International Conference on Software Defined Systems (SDS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W2163605009","https://openalex.org/W2754666677","https://openalex.org/W3087549734","https://openalex.org/W3181236787","https://openalex.org/W3186289373","https://openalex.org/W4207076279","https://openalex.org/W4239943352","https://openalex.org/W4302028668","https://openalex.org/W4318185327","https://openalex.org/W6684191040","https://openalex.org/W6783292247"],"related_works":["https://openalex.org/W4299822940","https://openalex.org/W2279398222","https://openalex.org/W3011074480","https://openalex.org/W4311257506","https://openalex.org/W3156786002","https://openalex.org/W4366492315","https://openalex.org/W2337926734","https://openalex.org/W4366224123","https://openalex.org/W2732542196","https://openalex.org/W2946016983"],"abstract_inverted_index":{"Automatic":[0],"person":[1],"recognition":[2,53,66,85,116,131],"systems":[3],"are":[4],"mainly":[5],"based":[6,55,132],"on":[7,56,133],"biometrics":[8,130],"traits":[9,136],"to":[10,21,121,146],"authenticate":[11],"or":[12],"identify":[13],"people":[14],"in":[15,35,51],"different":[16],"real-life":[17],"cases.":[18],"In":[19,38],"order":[20],"get":[22],"reliable":[23],"results,":[24],"all":[25],"the":[26,40,64,90,123],"web":[27],"giants":[28],"prioritize":[29],"investing":[30],"huge":[31],"sums":[32],"of":[33,43,83,92,125],"money":[34],"these":[36],"studies.":[37],"2019,":[39],"National":[41],"Institute":[42],"Standards":[44],"and":[45,106,141,144],"Technology":[46],"(NIST)":[47],"published":[48],"outstanding":[49],"achievements":[50],"facial":[52,57,65],"technology":[54],"biometrics.":[58],"One":[59],"recent":[60],"study":[61,122],"estimates":[62],"that":[63],"market":[67],"will":[68],"be":[69],"worth":[70],"8":[71],"billion":[72],"euros":[73],"by":[74,89],"2024,":[75],"with":[76],"double-digit":[77],"annual":[78],"growth":[79],"rates.":[80],"The":[81],"success":[82],"biometric":[84,115,135,154],"has":[86],"been":[87],"driven":[88],"advent":[91],"neural":[93,127],"networks":[94,128],"such":[95],"as":[96,138],"deep":[97],"learning":[98,101,150],"architectures.":[99],"These":[100],"methods":[102],"quickly":[103],"become":[104],"popular":[105],"have":[107],"offered":[108],"an":[109],"interesting":[110],"solution":[111],"for":[112,129,152],"realizing":[113],"intelligent":[114],"systems.":[117],"Our":[118],"work":[119],"aims":[120],"use":[124],"convolutional":[126],"various":[134],"(such":[137],"face,":[139],"palmprint,":[140],"palm":[142],"vein),":[143],"also":[145],"design":[147],"a":[148],"multi-task":[149],"model":[151],"multimodal":[153],"recognition,":[155]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}