{"id":"https://openalex.org/W3030380536","doi":"https://doi.org/10.1109/tip.2021.3061932","title":"Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild","display_name":"Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3030380536","doi":"https://doi.org/10.1109/tip.2021.3061932","mag":"3030380536","pmid":"https://pubmed.ncbi.nlm.nih.gov/33661733"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2021.3061932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3061932","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2005.13983","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Weixia Zhang","orcid":"https://orcid.org/0000-0002-3634-2630"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixia Zhang","raw_affiliation_strings":["MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-3634-2630","affiliations":[{"raw_affiliation_string":"MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kede Ma","orcid":"https://orcid.org/0000-0001-8608-1128"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kede Ma","raw_affiliation_strings":["City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-8608-1128","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guangtao Zhai","orcid":"https://orcid.org/0000-0001-8165-9322"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangtao Zhai","raw_affiliation_strings":["MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8165-9322","affiliations":[{"raw_affiliation_string":"MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xiaokang Yang","orcid":"https://orcid.org/0000-0003-4029-3322"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaokang Yang","raw_affiliation_strings":["MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4029-3322","affiliations":[{"raw_affiliation_string":"MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":19.3147,"has_fulltext":true,"cited_by_count":302,"citation_normalized_percentile":{"value":0.99629746,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"30","issue":null,"first_page":"3474","last_page":"3486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9714999794960022,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9714999794960022,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.008799999952316284,"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/T11019","display_name":"Image Enhancement Techniques","score":0.0038999998942017555,"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/image-quality","display_name":"Image quality","score":0.7002999782562256},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5916000008583069},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5105000138282776},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4968999922275543},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4796999990940094},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47940000891685486},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.47119998931884766},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4133000075817108},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3995000123977661}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7437000274658203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7053999900817871},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.7002999782562256},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5916000008583069},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.526199996471405},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5105000138282776},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4968999922275543},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4796999990940094},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47940000891685486},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.47119998931884766},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4092999994754791},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3995000123977661},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.390500009059906},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3808000087738037},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.36739999055862427},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.34310001134872437},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.31779998540878296},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3174000084400177},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.2921999990940094},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C39891107","wikidata":"https://www.wikidata.org/wiki/Q5767098","display_name":"Hinge loss","level":3,"score":0.26750001311302185},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.26489999890327454},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2646999955177307}],"mesh":[{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007753","descriptor_name":"Laboratories","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007753","descriptor_name":"Laboratories","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007753","descriptor_name":"Laboratories","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2021.3061932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3061932","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:33661733","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33661733","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:arXiv.org:2005.13983","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.13983","pdf_url":"https://arxiv.org/pdf/2005.13983","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:2005.13983","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.13983","pdf_url":"https://arxiv.org/pdf/2005.13983","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":[],"awards":[{"id":"https://openalex.org/G1978429096","display_name":null,"funder_award_id":"U19B2035","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3796158880","display_name":"\u9762\u5411\u590d\u6742\u573a\u666f\u7684\u591a\u66dd\u5149\u56fe\u50cf\u878d\u5408\u8d28\u91cf\u8bc4\u4ef7\u53ca\u5176\u611f\u77e5\u4f18\u5316","funder_award_id":"62071407","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5404748735","display_name":null,"funder_award_id":"61901262","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8250733612","display_name":null,"funder_award_id":"2021SHZDZX0102","funder_id":"https://openalex.org/F4320335480","funder_display_name":"Guangzhou Municipal Science and Technology Project"}],"funders":[{"id":"https://openalex.org/F4320309893","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335480","display_name":"Guangzhou Municipal Science and Technology Project","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3030380536.pdf","grobid_xml":"https://content.openalex.org/works/W3030380536.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1580389772","https://openalex.org/W1677182931","https://openalex.org/W1974013408","https://openalex.org/W1977725648","https://openalex.org/W1979451680","https://openalex.org/W1982471090","https://openalex.org/W2033442452","https://openalex.org/W2051596736","https://openalex.org/W2059283460","https://openalex.org/W2102166818","https://openalex.org/W2104657103","https://openalex.org/W2108598243","https://openalex.org/W2114338738","https://openalex.org/W2129644086","https://openalex.org/W2138790992","https://openalex.org/W2148848374","https://openalex.org/W2151035455","https://openalex.org/W2161907179","https://openalex.org/W2171349048","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2473697052","https://openalex.org/W2556068545","https://openalex.org/W2563786098","https://openalex.org/W2581944749","https://openalex.org/W2618902759","https://openalex.org/W2620678416","https://openalex.org/W2768340063","https://openalex.org/W2891645170","https://openalex.org/W2892006951","https://openalex.org/W2905544033","https://openalex.org/W2906729185","https://openalex.org/W2914547694","https://openalex.org/W2944282338","https://openalex.org/W2953590133","https://openalex.org/W2963918210","https://openalex.org/W2963975576","https://openalex.org/W2970763616","https://openalex.org/W3002992380","https://openalex.org/W3017136408","https://openalex.org/W3022710784","https://openalex.org/W3035595647","https://openalex.org/W3035712445","https://openalex.org/W3087520358","https://openalex.org/W3090767700","https://openalex.org/W4211253871","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6647225686","https://openalex.org/W6676199892","https://openalex.org/W6735443497","https://openalex.org/W6774563823","https://openalex.org/W6775547238"],"related_works":[],"abstract_inverted_index":{"Performance":[0],"of":[1,15,69,82,96,100,121,147,167],"blind":[2],"image":[3,95,123,154],"quality":[4,19,155],"assessment":[5],"(BIQA)":[6],"models":[7,38],"has":[8],"been":[9],"significantly":[10],"boosted":[11],"by":[12,172],"end-to-end":[13],"optimization":[14],"feature":[16],"engineering":[17],"and":[18,33,66,75,88,159],"regression.":[20],"Nevertheless,":[21],"due":[22],"to":[23,109,132,175],"the":[24,31,36,57,93,106,145,148,157,165,168],"distributional":[25],"shift":[26],"between":[27],"images":[28,83],"simulated":[29],"in":[30,35,151,156],"laboratory":[32,158],"captured":[34],"wild,":[37],"trained":[39],"on":[40,140],"databases":[41,143],"with":[42],"synthetic":[43,74],"distortions":[44,51],"remain":[45],"particularly":[46],"weak":[47],"at":[48],"handling":[49],"realistic":[50,76],"(and":[52],"vice":[53],"versa).":[54],"To":[55],"confront":[56],"cross-distortion-scenario":[58],"challenge,":[59],"we":[60,163],"develop":[61],"a":[62,90,111,118,129],"unified":[63],"BIQA":[64,116,178],"model":[65],"an":[67],"approach":[68],"training":[70,170],"it":[71,174],"for":[72,115],"both":[73],"distortions.":[77],"We":[78,103,125],"first":[79,94],"sample":[80],"pairs":[81],"from":[84],"individual":[85],"IQA":[86,142],"databases,":[87],"compute":[89],"probability":[91],"that":[92],"each":[97],"pair":[98],"is":[99],"higher":[101],"quality.":[102],"then":[104],"employ":[105],"fidelity":[107],"loss":[108],"optimize":[110],"deep":[112],"neural":[113],"network":[114],"over":[117],"large":[119],"number":[120],"such":[122],"pairs.":[124],"also":[126],"explicitly":[127],"enforce":[128],"hinge":[130],"constraint":[131],"regularize":[133],"uncertainty":[134],"estimation":[135],"during":[136],"optimization.":[137],"Extensive":[138],"experiments":[139],"six":[141],"show":[144],"promise":[146],"learned":[149],"method":[150],"blindly":[152],"assessing":[153],"wild.":[160],"In":[161],"addition,":[162],"demonstrate":[164],"universality":[166],"proposed":[169],"strategy":[171],"using":[173],"improve":[176],"existing":[177],"models.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":23},{"year":2025,"cited_by_count":74},{"year":2024,"cited_by_count":73},{"year":2023,"cited_by_count":59},{"year":2022,"cited_by_count":50},{"year":2021,"cited_by_count":23}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2020-06-05T00:00:00"}
