{"id":"https://openalex.org/W2934198733","doi":"https://doi.org/10.1109/tip.2020.3002345","title":"FoveaBox: Beyound Anchor-Based Object Detection","display_name":"FoveaBox: Beyound Anchor-Based Object Detection","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2934198733","doi":"https://doi.org/10.1109/tip.2020.3002345","mag":"2934198733"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2020.3002345","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3002345","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"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1904.03797","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Tao Kong","orcid":"https://orcid.org/0000-0002-9412-1457"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tao Kong","raw_affiliation_strings":["ByteDance AI Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"ByteDance AI Lab, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Fuchun Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuchun Sun","raw_affiliation_strings":["Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Huaping Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaping Liu","raw_affiliation_strings":["Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuning Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuning Jiang","raw_affiliation_strings":["ByteDance AI Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"ByteDance AI Lab, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Li","raw_affiliation_strings":["ByteDance AI Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"ByteDance AI Lab, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Jianbo Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianbo Shi","raw_affiliation_strings":["GRASP Laboratory, University of Pennsylvania, Philadelphia, USA"],"affiliations":[{"raw_affiliation_string":"GRASP Laboratory, University of Pennsylvania, Philadelphia, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":55.2564,"has_fulltext":false,"cited_by_count":890,"citation_normalized_percentile":{"value":0.99933689,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"29","issue":null,"first_page":"7389","last_page":"7398"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8992000222206116,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.8992000222206116,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.027499999850988388,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.013199999928474426,"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/object-detection","display_name":"Object detection","score":0.8294000029563904},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.8061000108718872},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.7935000061988831},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.517300009727478},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4934000074863434},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48010000586509705},{"id":"https://openalex.org/keywords/viola\u2013jones-object-detection-framework","display_name":"Viola\u2013Jones object detection framework","score":0.4763000011444092},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47049999237060547}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.8294000029563904},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.8061000108718872},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.7935000061988831},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7371000051498413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5924999713897705},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.517300009727478},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5070000290870667},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4934000074863434},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48010000586509705},{"id":"https://openalex.org/C182521987","wikidata":"https://www.wikidata.org/wiki/Q2493877","display_name":"Viola\u2013Jones object detection framework","level":5,"score":0.4763000011444092},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47049999237060547},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4632999897003174},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45899999141693115},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.43309998512268066},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.39149999618530273},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37130001187324524},{"id":"https://openalex.org/C71681937","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object-class detection","level":5,"score":0.37040001153945923},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.36730000376701355},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.29660001397132874},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2020.3002345","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3002345","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":"pmh:oai:arXiv.org:1904.03797","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.03797","pdf_url":"https://arxiv.org/pdf/1904.03797","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:1904.03797","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.03797","pdf_url":"https://arxiv.org/pdf/1904.03797","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/G1023919524","display_name":null,"funder_award_id":", Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1566444292","display_name":null,"funder_award_id":"21136008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1919465925","display_name":null,"funder_award_id":"61621136008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3355224328","display_name":null,"funder_award_id":"61621136008","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G3449269236","display_name":null,"funder_award_id":"DFG TRR-169","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G3692375717","display_name":null,"funder_award_id":"91848206","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4450327046","display_name":null,"funder_award_id":"91848206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5244829453","display_name":null,"funder_award_id":"TRR-169","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6093743924","display_name":"CPS: Medium: Collaborative Research: Credible Autocoding and Verification of Embedded Software (CrAVES)","funder_award_id":"1136008","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7226905331","display_name":null,"funder_award_id":"TRR-169","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G7440672857","display_name":null,"funder_award_id":"U1613212","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G966766036","display_name":null,"funder_award_id":"U1613212","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W166750225","https://openalex.org/W1536680647","https://openalex.org/W1903029394","https://openalex.org/W1932624639","https://openalex.org/W2031489346","https://openalex.org/W2036989445","https://openalex.org/W2102605133","https://openalex.org/W2113201641","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2168356304","https://openalex.org/W2194775991","https://openalex.org/W2288122362","https://openalex.org/W2339589954","https://openalex.org/W2358876993","https://openalex.org/W2402144811","https://openalex.org/W2504335775","https://openalex.org/W2512351403","https://openalex.org/W2548197316","https://openalex.org/W2557728737","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2601564443","https://openalex.org/W2605982830","https://openalex.org/W2884561390","https://openalex.org/W2886904239","https://openalex.org/W2888728082","https://openalex.org/W2944938209","https://openalex.org/W2962917547","https://openalex.org/W2962992847","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963179609","https://openalex.org/W2963299996","https://openalex.org/W2963446712","https://openalex.org/W2963516811","https://openalex.org/W2963786238","https://openalex.org/W2963813458","https://openalex.org/W2963927307","https://openalex.org/W2964080601","https://openalex.org/W2964121718","https://openalex.org/W2964241181","https://openalex.org/W2965318645","https://openalex.org/W2982770724","https://openalex.org/W2986357608","https://openalex.org/W2988452521","https://openalex.org/W2989604896","https://openalex.org/W3012573144","https://openalex.org/W6607196103","https://openalex.org/W6620707391","https://openalex.org/W6629368666","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6679461745","https://openalex.org/W6684191040","https://openalex.org/W6730410022","https://openalex.org/W6731615698","https://openalex.org/W6732243160","https://openalex.org/W6750227808","https://openalex.org/W6752745451","https://openalex.org/W6754632766","https://openalex.org/W6756800942","https://openalex.org/W6756817110","https://openalex.org/W6758453640","https://openalex.org/W6760424586","https://openalex.org/W6766548695","https://openalex.org/W6766978945","https://openalex.org/W6770600958","https://openalex.org/W6772372853","https://openalex.org/W6775059118","https://openalex.org/W6775292734","https://openalex.org/W6775367004","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2975200075","https://openalex.org/W2325242284","https://openalex.org/W2007544051","https://openalex.org/W1837097281","https://openalex.org/W2095705906","https://openalex.org/W1966410754","https://openalex.org/W1569815043","https://openalex.org/W2030539674","https://openalex.org/W2789220062","https://openalex.org/W2755342338"],"abstract_inverted_index":{"We":[0,173],"present":[1],"FoveaBox,":[2,106],"an":[3,91,107],"accurate,":[4],"flexible,":[5],"and":[6,27,38,57,79,127,134,146,158,177,186],"completely":[7],"anchor-free":[8],"framework":[9],"for":[10,30,74,85,191],"object":[11,17,54,76,149,192],"detection.":[12,193],"While":[13],"almost":[14],"all":[15,156],"state-of-the-art":[16,138],"detectors":[18],"utilize":[19],"predefined":[20],"anchors":[21],"to":[22,44,111,115,161,168],"enumerate":[23],"possible":[24],"locations,":[25],"scales":[26,94],"aspect":[28],"ratios":[29],"the":[31,34,45,53,58,75,117,143,169,175],"search":[32],"of":[33,47,95],"objects,":[35],"their":[36],"performance":[37,141],"generalization":[39],"ability":[40],"are":[41,98,165],"also":[42],"limited":[43],"design":[46],"anchors.":[48],"Instead,":[49],"FoveaBox":[50,136,154],"directly":[51],"learns":[52],"existing":[55,77],"possibility":[56],"bounding":[59,83],"box":[60,84],"coordinates":[61],"without":[62],"anchor":[63,162],"reference.":[64],"This":[65],"is":[66,109],"achieved":[67],"by:":[68],"(a)":[69],"predicting":[70],"category-sensitive":[71],"semantic":[72],"maps":[73],"possibility,":[78],"(b)":[80],"producing":[81],"category-agnostic":[82],"each":[86],"position":[87],"that":[88],"potentially":[89],"contains":[90],"object.":[92],"The":[93,194],"target":[96],"boxes":[97],"naturally":[99],"associated":[100],"with":[101],"feature":[102,113],"pyramid":[103],"representations.":[104],"In":[105],"instance":[108],"assigned":[110],"adjacent":[112],"levels":[114],"make":[116],"model":[118,140],"more":[119],"accurate.We":[120],"demonstrate":[121],"its":[122],"effectiveness":[123],"on":[124,142],"standard":[125,144],"benchmarks":[126],"report":[128],"extensive":[129],"experimental":[130],"analysis.":[131],"Without":[132],"bells":[133],"whistles,":[135],"achieves":[137],"single":[139],"COCO":[145],"Pascal":[147],"VOC":[148],"detection":[150,171],"benchmark.":[151],"More":[152],"importantly,":[153],"avoids":[155],"computation":[157],"hyper-parameters":[159],"related":[160],"boxes,":[163],"which":[164],"often":[166],"sensitive":[167],"final":[170],"performance.":[172],"believe":[174],"simple":[176],"effective":[178],"approach":[179],"will":[180],"serve":[181],"as":[182],"a":[183],"solid":[184],"baseline":[185],"help":[187],"ease":[188],"future":[189],"research":[190],"code":[195],"has":[196],"been":[197],"made":[198],"publicly":[199],"available":[200],"at":[201],"<uri":[202],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[203],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/taokong/FoveaBox</uri>":[204],".":[205]},"counts_by_year":[{"year":2026,"cited_by_count":23},{"year":2025,"cited_by_count":126},{"year":2024,"cited_by_count":176},{"year":2023,"cited_by_count":196},{"year":2022,"cited_by_count":199},{"year":2021,"cited_by_count":135},{"year":2020,"cited_by_count":33},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2019-04-11T00:00:00"}
