{"id":"https://openalex.org/W2888049721","doi":"https://doi.org/10.1109/saci.2018.8441009","title":"Granular Computing and Sequential Analysis of Deep Embeddings in Fast Still-to-Video Face Recognition","display_name":"Granular Computing and Sequential Analysis of Deep Embeddings in Fast Still-to-Video Face Recognition","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2888049721","doi":"https://doi.org/10.1109/saci.2018.8441009","mag":"2888049721"},"language":"en","primary_location":{"id":"doi:10.1109/saci.2018.8441009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/saci.2018.8441009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)","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/A5016964202","display_name":"A. Savchenko","orcid":"https://orcid.org/0000-0001-6196-0564"},"institutions":[{"id":"https://openalex.org/I118501908","display_name":"National Research University Higher School of Economics","ror":"https://ror.org/055f7t516","country_code":"RU","type":"education","lineage":["https://openalex.org/I118501908"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Andrey V. Savchenko","raw_affiliation_strings":["Laboratory of Algorithms and Technologies for Network Analysis, National Research University Higher School of Economics, Nizhny Novgorod, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Algorithms and Technologies for Network Analysis, National Research University Higher School of Economics, Nizhny Novgorod, Russia","institution_ids":["https://openalex.org/I118501908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5016964202"],"corresponding_institution_ids":["https://openalex.org/I118501908"],"apc_list":null,"apc_paid":null,"fwci":0.3042,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.66340437,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3400","issue":null,"first_page":"000515","last_page":"000520"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9998000264167786,"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/T10057","display_name":"Face and Expression Recognition","score":0.9998000264167786,"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/T11448","display_name":"Face recognition and analysis","score":0.9991999864578247,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/computer-science","display_name":"Computer science","score":0.7770002484321594},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.7280350923538208},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7003719210624695},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5865200757980347},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5762799978256226},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5595753788948059},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.556825578212738},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5138314366340637},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47832751274108887},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.43869689106941223},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43500712513923645},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.42154461145401},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4193430244922638},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.41721677780151367},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38045433163642883},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2347751259803772},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2070084810256958}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770002484321594},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.7280350923538208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7003719210624695},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5865200757980347},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5762799978256226},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5595753788948059},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.556825578212738},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5138314366340637},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47832751274108887},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.43869689106941223},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43500712513923645},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.42154461145401},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4193430244922638},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41721677780151367},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38045433163642883},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2347751259803772},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2070084810256958},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/saci.2018.8441009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/saci.2018.8441009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)","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":0.7400000095367432}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324261","display_name":"National Research University Higher School of Economics","ror":"https://ror.org/055f7t516"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W69471719","https://openalex.org/W95749022","https://openalex.org/W297279189","https://openalex.org/W1461115072","https://openalex.org/W1703179648","https://openalex.org/W1861960977","https://openalex.org/W1949778830","https://openalex.org/W1968678306","https://openalex.org/W1970604134","https://openalex.org/W2019464758","https://openalex.org/W2043994465","https://openalex.org/W2075933837","https://openalex.org/W2084890760","https://openalex.org/W2108767394","https://openalex.org/W2111654153","https://openalex.org/W2112000778","https://openalex.org/W2112695787","https://openalex.org/W2123838014","https://openalex.org/W2141425367","https://openalex.org/W2142185590","https://openalex.org/W2143159002","https://openalex.org/W2151103935","https://openalex.org/W2158275940","https://openalex.org/W2206837713","https://openalex.org/W2275811363","https://openalex.org/W2287358502","https://openalex.org/W2304348237","https://openalex.org/W2325939864","https://openalex.org/W2336258321","https://openalex.org/W2474608001","https://openalex.org/W2481024011","https://openalex.org/W2706729717","https://openalex.org/W2755621335","https://openalex.org/W2796645997","https://openalex.org/W2963559058","https://openalex.org/W2963570419","https://openalex.org/W2963839617","https://openalex.org/W3101036461","https://openalex.org/W3105605827","https://openalex.org/W3145164839","https://openalex.org/W4246070010","https://openalex.org/W6602791602","https://openalex.org/W6628466913","https://openalex.org/W6678511256","https://openalex.org/W6680911227","https://openalex.org/W6697959347","https://openalex.org/W6700903540"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W4382701072","https://openalex.org/W4256502920","https://openalex.org/W2491314273"],"abstract_inverted_index":{"This":[0],"paper":[1],"is":[2,69,91,151,173],"focused":[3],"on":[4,14],"still-to-video":[5],"face":[6],"recognition":[7],"with":[8,71,130,156],"large":[9],"number":[10,51],"of":[11,16,38,41,52,57,62,74,76,97,114,143],"subjects":[12],"based":[13],"computation":[15],"distances":[17],"between":[18,99],"high-dimensional":[19],"embeddings":[20,167],"extracted":[21],"using":[22],"deep":[23,58,166],"convolution":[24],"neural":[25],"networks.":[26],"We":[27],"propose":[28],"to":[29,105],"utilize":[30],"granular":[31,36],"structures":[32],"and":[33,102,145,160,163],"sequentially":[34],"process":[35],"representations":[37,73],"all":[39,115,135],"frames":[40,136],"the":[42,53,72,82,95,106,112,127,146,157,164,170],"input":[43,103],"video.":[44],"The":[45,60,89,153],"coarse-grained":[46],"granules":[47],"include":[48],"only":[49,77],"low":[50],"first":[54],"principal":[55],"components":[56],"embeddings.":[59],"representation":[61],"each":[63],"frame":[64,104,125],"at":[65,84,126],"finer":[66,131],"granularity":[67],"levels":[68,86,129],"matched":[70],"photos":[75,113],"those":[78],"individuals,":[79],"for":[80,122,134],"whom":[81],"decision":[83,150],"previous":[85],"was":[87],"reliable.":[88],"reliability":[90],"checked":[92],"by":[93],"thresholding":[94],"ratio":[96],"distance":[98],"reference":[100],"instance":[101],"minimal":[107],"distance.":[108],"As":[109],"a":[110,123,140],"result,":[111],"unreliable":[116],"individuals":[117],"are":[118,137],"not":[119],"examined":[120],"anymore":[121],"particular":[124],"next":[128],"granularity.":[132],"Decisions":[133],"united":[138],"into":[139],"candidate":[141],"set":[142],"identities,":[144],"maximal":[147],"a-posterior":[148],"final":[149],"chosen.":[152],"experimental":[154],"study":[155],"LFW,":[158],"YTF":[159],"IJB-A":[161],"datasets":[162],"state-of-the-art":[165],"demonstrated":[168],"that":[169],"proposed":[171],"approach":[172],"2-10":[174],"times":[175],"faster":[176],"than":[177],"conventional":[178],"methods.":[179]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}