{"id":"https://openalex.org/W4280647163","doi":"https://doi.org/10.1142/s0219467823500298","title":"A New Design of Occlusion-Invariant Face Recognition Using Optimal Pattern Extraction and CNN with GRU-Based Architecture","display_name":"A New Design of Occlusion-Invariant Face Recognition Using Optimal Pattern Extraction and CNN with GRU-Based Architecture","publication_year":2022,"publication_date":"2022-05-11","ids":{"openalex":"https://openalex.org/W4280647163","doi":"https://doi.org/10.1142/s0219467823500298"},"language":"en","primary_location":{"id":"doi:10.1142/s0219467823500298","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467823500298","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-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":null,"display_name":"Pankaj","orcid":null},"institutions":[{"id":"https://openalex.org/I139858224","display_name":"M.J.P. Rohilkhand University","ror":"https://ror.org/02e3nay30","country_code":"IN","type":"education","lineage":["https://openalex.org/I139858224"]},{"id":"https://openalex.org/I15517640","display_name":"Shri Venkateshwara University","ror":"https://ror.org/00xh8va68","country_code":"IN","type":"education","lineage":["https://openalex.org/I15517640"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Pankaj","raw_affiliation_strings":["Department of CS&IT, MJP Rohilkhand University, Bareilly 243006, Uttar Pradesh, India","Shri Venkateshwara University, Amroha, Venkateshwara Nagar, Gajraula, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of CS&IT, MJP Rohilkhand University, Bareilly 243006, Uttar Pradesh, India","institution_ids":["https://openalex.org/I139858224"]},{"raw_affiliation_string":"Shri Venkateshwara University, Amroha, Venkateshwara Nagar, Gajraula, Uttar Pradesh, India","institution_ids":["https://openalex.org/I15517640"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080990691","display_name":"Prabhat Kumar Bharti","orcid":"https://orcid.org/0000-0002-9288-2391"},"institutions":[{"id":"https://openalex.org/I15517640","display_name":"Shri Venkateshwara University","ror":"https://ror.org/00xh8va68","country_code":"IN","type":"education","lineage":["https://openalex.org/I15517640"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"P. K. Bharti","raw_affiliation_strings":["Department of Computer Science and Engineering, School of Engineering and Technology, Shri Venkateshwara University, Amroha 244236, UP, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, School of Engineering and Technology, Shri Venkateshwara University, Amroha 244236, UP, India","institution_ids":["https://openalex.org/I15517640"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045463867","display_name":"Brajesh Kumar","orcid":"https://orcid.org/0000-0001-8100-7287"},"institutions":[{"id":"https://openalex.org/I139858224","display_name":"M.J.P. Rohilkhand University","ror":"https://ror.org/02e3nay30","country_code":"IN","type":"education","lineage":["https://openalex.org/I139858224"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Brajesh Kumar","raw_affiliation_strings":["Department of CS&IT, MJP Rohilkhand University, Bareilly 243006, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of CS&IT, MJP Rohilkhand University, Bareilly 243006, Uttar Pradesh, India","institution_ids":["https://openalex.org/I139858224"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139858224","https://openalex.org/I15517640"],"apc_list":null,"apc_paid":null,"fwci":0.2042,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46294909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"23","issue":"04","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9948999881744385,"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/T10828","display_name":"Biometric Identification and Security","score":0.9789999723434448,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8154492974281311},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.77824866771698},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6450083255767822},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6264734864234924},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6032447814941406},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4710274338722229},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.418212354183197},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.418088436126709},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1702161431312561},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.08102244138717651}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8154492974281311},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.77824866771698},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6450083255767822},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6264734864234924},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6032447814941406},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4710274338722229},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.418212354183197},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.418088436126709},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1702161431312561},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.08102244138717651}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0219467823500298","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467823500298","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1721634477","https://openalex.org/W1923816111","https://openalex.org/W1983474530","https://openalex.org/W1988178499","https://openalex.org/W2043661478","https://openalex.org/W2052503369","https://openalex.org/W2075708095","https://openalex.org/W2109685970","https://openalex.org/W2126074213","https://openalex.org/W2144035585","https://openalex.org/W2191588813","https://openalex.org/W2504414453","https://openalex.org/W2561648494","https://openalex.org/W2604976973","https://openalex.org/W2618825926","https://openalex.org/W2806872289","https://openalex.org/W2888971264","https://openalex.org/W2918254569","https://openalex.org/W2963809521","https://openalex.org/W2964023530","https://openalex.org/W2999693455","https://openalex.org/W2999814961","https://openalex.org/W3002624958","https://openalex.org/W3008345160","https://openalex.org/W3020688348","https://openalex.org/W3086218926","https://openalex.org/W3096199586","https://openalex.org/W3104211051","https://openalex.org/W3134321748","https://openalex.org/W3134419444","https://openalex.org/W3150907838","https://openalex.org/W3158004940","https://openalex.org/W3186458945","https://openalex.org/W3198630344","https://openalex.org/W3201377238","https://openalex.org/W3214290191"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W3211626993","https://openalex.org/W1976280679","https://openalex.org/W1978011637","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2122718025","https://openalex.org/W2169521742","https://openalex.org/W4383117988","https://openalex.org/W2900460335"],"abstract_inverted_index":{"Face":[0],"detection":[1],"is":[2,36,102,113,164,178,195,235,256],"a":[3,9,32,109,155,281],"computer":[4],"technology":[5],"being":[6],"used":[7,196,236],"in":[8,17,46,67,96,118,246,311],"variety":[10],"of":[11,43,63,73,92,161,248,289],"applications":[12],"that":[13],"identify":[14],"human":[15],"faces":[16],"digital":[18],"images.":[19],"In":[20],"many":[21,294],"face":[22,44,55,74,148,240,299,308],"recognition":[23,45,56,226,241,300,309],"challenges,":[24],"Convolutional":[25],"Neural":[26],"Networks":[27],"(CNNs)":[28],"are":[29,51,81,152,273],"regarded":[30],"as":[31,38],"problem":[33],"solver.":[34],"Occlusion":[35],"determined":[37],"the":[39,61,68,71,86,90,97,122,147,159,162,181,188,199,208,211,225,230,239,244,250,264,287,290,312],"most":[40],"common":[41],"challenge":[42],"realistic":[47],"applications.":[48],"Several":[49],"studies":[50,80],"undergoing":[52],"to":[53,84,104,115,228,237,298,307],"obtain":[54],"without":[57],"any":[58],"challenges.":[59],"However,":[60,293],"occurrence":[62,91],"noise":[64,95],"and":[65,79,94,99,140,169,232,261,267,284],"occlusion":[66,93,151],"image":[69,149],"reduces":[70],"achievement":[72],"recognition.":[75],"Hence,":[76,108],"various":[77],"researches":[78],"carried":[82],"out":[83],"solve":[85],"challenges":[87],"involved":[88],"with":[89,150,218],"image,":[98,210],"more":[100],"clarification":[101],"needed":[103],"acquire":[105],"high":[106],"accuracy.":[107],"deep":[110,213],"learning":[111,214],"model":[112,127,215,255],"intended":[114],"be":[116],"developed":[117],"this":[119],"paper":[120],"using":[121],"meta-heuristic":[123],"approach.":[124],"The":[125,143,270],"proposed":[126,251,291],"covers":[128],"four":[129],"main":[130],"steps:":[131],"(a)":[132],"data":[133],"acquisition,":[134],"(b)":[135],"pre-processing,":[136],"(c)":[137],"pattern":[138,176,204],"extraction":[139,177],"(d)":[141],"classification.":[142],"benchmark":[144],"datasets":[145],"regarding":[146],"gathered":[153],"from":[154],"public":[156],"source.":[157],"Further,":[158],"pre-processing":[160],"images":[163],"performed":[165],"by":[166,180,258,275],"contrast":[167],"enhancement":[168],"Gabor":[170],"filtering.":[171],"With":[172],"these":[173],"pre-processed":[174],"images,":[175],"done":[179],"optimal":[182,200],"local":[183,201],"mesh":[184,202],"ternary":[185,203],"pattern.":[186],"Here,":[187],"hybrid":[189],"Whale\u2013Galactic":[190],"Swarm":[191],"Optimization":[192],"(WGSO)":[193],"algorithm":[194],"for":[197],"developing":[198],"extraction.":[205],"By":[206],"inputting":[207],"pattern-extracted":[209],"new":[212],"namely":[216],"\u201cCNN":[217],"Gated":[219],"Recurrent":[220],"Unit":[221],"(GRU)\u201d":[222],"network":[223],"performs":[224],"process":[227],"maximize":[229],"accuracy,":[231,249],"also":[233],"it":[234],"enhance":[238],"model.":[242,292],"From":[243],"results,":[245],"terms":[247],"WGSO-[Formula:":[252],"see":[253],"text]":[254],"better":[257],"4.02%,":[259],"3.76%":[260],"2.17%":[262],"than":[263],"CNN,":[265],"SVM":[266],"SRC,":[268],"respectively.":[269],"experimental":[271],"results":[272],"presented":[274],"performing":[276],"their":[277],"comparative":[278],"analysis":[279],"on":[280],"standard":[282],"dataset,":[283],"they":[285],"assure":[286],"efficiency":[288],"challenging":[295],"problems":[296],"related":[297],"still":[301],"exist,":[302],"which":[303],"offer":[304],"excellent":[305],"opportunities":[306],"researchers":[310],"future.":[313]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2022-05-22T00:00:00"}