{"id":"https://openalex.org/W4205603901","doi":"https://doi.org/10.1109/tai.2021.3139058","title":"A Survey on Masked Facial Detection Methods and Datasets for Fighting Against COVID-19","display_name":"A Survey on Masked Facial Detection Methods and Datasets for Fighting Against COVID-19","publication_year":2021,"publication_date":"2021-12-28","ids":{"openalex":"https://openalex.org/W4205603901","doi":"https://doi.org/10.1109/tai.2021.3139058"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2021.3139058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2021.3139058","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2201.04777","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042066946","display_name":"Bingshu Wang","orcid":"https://orcid.org/0000-0002-2603-8328"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bingshu Wang","raw_affiliation_strings":["School of Software, Taicang Campus, Northwestern Polytechnical University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Taicang Campus, Northwestern Polytechnical University, Suzhou, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100680277","display_name":"Jiangbin Zheng","orcid":"https://orcid.org/0000-0001-5943-7379"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangbin Zheng","raw_affiliation_strings":["School of Software, Taicang Campus, Northwestern Polytechnical University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Taicang Campus, Northwestern Polytechnical University, Suzhou, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100643265","display_name":"C. L. Philip Chen","orcid":"https://orcid.org/0000-0001-5451-7230"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"C. L. Philip Chen","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5042066946"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":2.8159,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.92352561,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"3","issue":"3","first_page":"323","last_page":"343"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9983999729156494,"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":0.9983999729156494,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9807000160217285,"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/T10990","display_name":"Infection Control and Ventilation","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7138140201568604},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6894771456718445},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6228227615356445},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6098688840866089},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5247811675071716},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.522869348526001},{"id":"https://openalex.org/keywords/severe-acute-respiratory-syndrome-coronavirus-2","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","score":0.4767407178878784},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46746543049812317},{"id":"https://openalex.org/keywords/2019-20-coronavirus-outbreak","display_name":"2019-20 coronavirus outbreak","score":0.4406563639640808},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.35825634002685547},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35429978370666504},{"id":"https://openalex.org/keywords/outbreak","display_name":"Outbreak","score":0.31637609004974365},{"id":"https://openalex.org/keywords/infectious-disease","display_name":"Infectious disease (medical specialty)","score":0.3154072165489197},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.17960882186889648},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10964512825012207},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.06704851984977722}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7138140201568604},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6894771456718445},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6228227615356445},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6098688840866089},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5247811675071716},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.522869348526001},{"id":"https://openalex.org/C3007834351","wikidata":"https://www.wikidata.org/wiki/Q82069695","display_name":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)","level":5,"score":0.4767407178878784},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46746543049812317},{"id":"https://openalex.org/C3006700255","wikidata":"https://www.wikidata.org/wiki/Q81068910","display_name":"2019-20 coronavirus outbreak","level":3,"score":0.4406563639640808},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35825634002685547},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35429978370666504},{"id":"https://openalex.org/C116675565","wikidata":"https://www.wikidata.org/wiki/Q3241045","display_name":"Outbreak","level":2,"score":0.31637609004974365},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.3154072165489197},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.17960882186889648},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10964512825012207},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.06704851984977722},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tai.2021.3139058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2021.3139058","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2201.04777","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.04777","pdf_url":"https://arxiv.org/pdf/2201.04777","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2201.04777","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.04777","pdf_url":"https://arxiv.org/pdf/2201.04777","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8700000047683716,"id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G1393196825","display_name":null,"funder_award_id":"62102318","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2353011048","display_name":null,"funder_award_id":"G2020KY05113","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G420612141","display_name":null,"funder_award_id":"U1801262","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5750115239","display_name":null,"funder_award_id":"U1813203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G653700208","display_name":null,"funder_award_id":"61751202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6741110764","display_name":null,"funder_award_id":"61702195","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7611596349","display_name":null,"funder_award_id":"61751205","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":163,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1135936395","https://openalex.org/W1834627138","https://openalex.org/W2039051707","https://openalex.org/W2153635508","https://openalex.org/W2160532515","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2164598857","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2341528187","https://openalex.org/W2509818455","https://openalex.org/W2603203130","https://openalex.org/W2738226240","https://openalex.org/W2739722733","https://openalex.org/W2769576731","https://openalex.org/W2786437580","https://openalex.org/W2884367402","https://openalex.org/W2885976210","https://openalex.org/W2890126432","https://openalex.org/W2893682050","https://openalex.org/W2940262938","https://openalex.org/W2962730651","https://openalex.org/W2962766044","https://openalex.org/W2962770929","https://openalex.org/W2963037989","https://openalex.org/W2963566548","https://openalex.org/W2963856926","https://openalex.org/W2989604896","https://openalex.org/W3001897055","https://openalex.org/W3005145900","https://openalex.org/W3010052540","https://openalex.org/W3010785824","https://openalex.org/W3012573144","https://openalex.org/W3013800799","https://openalex.org/W3018757597","https://openalex.org/W3021137017","https://openalex.org/W3021953217","https://openalex.org/W3022728207","https://openalex.org/W3024585647","https://openalex.org/W3026999132","https://openalex.org/W3034552680","https://openalex.org/W3044778821","https://openalex.org/W3045576536","https://openalex.org/W3047908376","https://openalex.org/W3048140877","https://openalex.org/W3070220677","https://openalex.org/W3080142342","https://openalex.org/W3090527447","https://openalex.org/W3091248836","https://openalex.org/W3091895534","https://openalex.org/W3092313915","https://openalex.org/W3092708662","https://openalex.org/W3093217433","https://openalex.org/W3093818734","https://openalex.org/W3094174933","https://openalex.org/W3095635545","https://openalex.org/W3096609285","https://openalex.org/W3097096317","https://openalex.org/W3097217077","https://openalex.org/W3097322459","https://openalex.org/W3097551614","https://openalex.org/W3101978680","https://openalex.org/W3101998545","https://openalex.org/W3105153358","https://openalex.org/W3106629518","https://openalex.org/W3109519692","https://openalex.org/W3109932136","https://openalex.org/W3109940015","https://openalex.org/W3110529155","https://openalex.org/W3112087292","https://openalex.org/W3113325168","https://openalex.org/W3114687924","https://openalex.org/W3115773619","https://openalex.org/W3115913152","https://openalex.org/W3118308958","https://openalex.org/W3120614410","https://openalex.org/W3121819577","https://openalex.org/W3124621411","https://openalex.org/W3125062334","https://openalex.org/W3126909071","https://openalex.org/W3126961265","https://openalex.org/W3127404911","https://openalex.org/W3127755597","https://openalex.org/W3128758033","https://openalex.org/W3129804828","https://openalex.org/W3130703804","https://openalex.org/W3132342445","https://openalex.org/W3133394266","https://openalex.org/W3133542101","https://openalex.org/W3133830781","https://openalex.org/W3134154885","https://openalex.org/W3135409251","https://openalex.org/W3135539855","https://openalex.org/W3135939397","https://openalex.org/W3137508402","https://openalex.org/W3138522453","https://openalex.org/W3138786299","https://openalex.org/W3142882742","https://openalex.org/W3143245897","https://openalex.org/W3147327871","https://openalex.org/W3149292000","https://openalex.org/W3152522844","https://openalex.org/W3153743799","https://openalex.org/W3154912261","https://openalex.org/W3155149625","https://openalex.org/W3155757473","https://openalex.org/W3156485287","https://openalex.org/W3157135149","https://openalex.org/W3157143019","https://openalex.org/W3159047500","https://openalex.org/W3159774911","https://openalex.org/W3161094615","https://openalex.org/W3162472108","https://openalex.org/W3162717069","https://openalex.org/W3162760148","https://openalex.org/W3165444657","https://openalex.org/W3167196982","https://openalex.org/W3169519640","https://openalex.org/W3174464158","https://openalex.org/W3174995574","https://openalex.org/W3175580333","https://openalex.org/W3176383825","https://openalex.org/W3176794744","https://openalex.org/W3177205550","https://openalex.org/W3177367688","https://openalex.org/W3182931234","https://openalex.org/W3183931335","https://openalex.org/W3184793223","https://openalex.org/W3185537204","https://openalex.org/W3187817180","https://openalex.org/W3191841357","https://openalex.org/W3193756932","https://openalex.org/W3194913784","https://openalex.org/W3195317227","https://openalex.org/W3196155740","https://openalex.org/W3196939630","https://openalex.org/W3208096854","https://openalex.org/W3210988591","https://openalex.org/W3215461129","https://openalex.org/W4206446419","https://openalex.org/W4286602937","https://openalex.org/W4287825176","https://openalex.org/W4293584584","https://openalex.org/W4297775537","https://openalex.org/W4321151695","https://openalex.org/W6684191040","https://openalex.org/W6737664043","https://openalex.org/W6746054350","https://openalex.org/W6750227808","https://openalex.org/W6761630670","https://openalex.org/W6776240797","https://openalex.org/W6777046832","https://openalex.org/W6782102408","https://openalex.org/W6790414147","https://openalex.org/W6791011037","https://openalex.org/W6794708578","https://openalex.org/W6799275916","https://openalex.org/W6800061013","https://openalex.org/W6800573535","https://openalex.org/W6879251957","https://openalex.org/W6959966577"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2378327072","https://openalex.org/W326517241"],"abstract_inverted_index":{"Coronavirus":[0],"disease":[1,39],"2019":[2],"(COVID-19)":[3],"continues":[4],"to":[5,10,32,59,69,163,228],"pose":[6],"a":[7,21,150],"great":[8],"challenge":[9],"the":[11,19,61,84,96,101,121,164,187,192,195,211],"world":[12],"since":[13],"its":[14],"outbreak.":[15],"To":[16,206],"fight":[17,229],"against":[18,230],"disease,":[20],"series":[22],"of":[23,47,63,73,87,103,110,166,197],"artificial":[24],"intelligence":[25],"(AI)":[26],"techniques":[27,86,179],"are":[28,114,123,138,156,171,181],"developed":[29],"and":[30,44,91,116,131,199,201,219],"applied":[31],"real-world":[33],"scenarios":[34],"such":[35],"as":[36,159],"safety":[37],"monitoring,":[38],"diagnosis,":[40],"infection":[41],"risk":[42],"assessment,":[43],"lesion":[45],"segmentation":[46],"COVID-19":[48],"CT":[49],"scans.":[50],"The":[51,135],"coronavirus":[52],"epidemics":[53],"have":[54],"forced":[55],"people":[56,74],"wear":[57],"masks":[58],"counteract":[60],"transmission":[62],"virus,":[64],"which":[65,147],"also":[66],"brings":[67],"difficulties":[68],"monitor":[70],"large":[71],"groups":[72],"wearing":[75],"masks.":[76],"In":[77],"this":[78,209],"article,":[79],"we":[80,185],"primarily":[81],"focus":[82],"on":[83,194],"AI":[85],"masked":[88,104,215],"facial":[89,105,216],"detection":[90,106,217],"related":[92],"datasets.":[93,107,220],"We":[94],"survey":[95,213,223],"recent":[97,188],"advances,":[98],"beginning":[99],"with":[100,144,176],"descriptions":[102],"A":[108],"total":[109],"13":[111],"available":[112],"datasets":[113,198],"described":[115,172,182],"discussed":[117],"in":[118,173],"detail.":[119],"Then,":[120],"methods":[122,130,137,155,218],"roughly":[124],"categorized":[125],"into":[126],"two":[127],"classes:":[128],"conventional":[129,136],"neural":[132],"network-based":[133,154],"methods.":[134],"usually":[139],"trained":[140],"by":[141],"boosting":[142],"algorithms":[143,170],"hand-crafted":[145],"features,":[146],"accounts":[148],"for":[149],"small":[151],"proportion.":[152],"Neural":[153],"further":[157],"classified":[158],"three":[160],"parts":[161],"according":[162],"number":[165],"processing":[167],"stages.":[168],"Representative":[169],"detail,":[174],"coupled":[175],"some":[177,226],"typical":[178],"that":[180],"briefly.":[183],"Finally,":[184],"summarize":[186],"benchmarking":[189],"results,":[190],"give":[191],"discussions":[193],"limitations":[196],"methods,":[200],"expand":[202],"future":[203],"research":[204],"directions.":[205],"our":[207,222],"knowledge,":[208],"is":[210],"first":[212],"about":[214],"Hopefully":[221],"could":[224],"provide":[225],"help":[227],"epidemics.":[231]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":10}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
