{"id":"https://openalex.org/W3048180155","doi":"https://doi.org/10.3390/s20164430","title":"Pine Cone Detection Using Boundary Equilibrium Generative Adversarial Networks and Improved YOLOv3 Model","display_name":"Pine Cone Detection Using Boundary Equilibrium Generative Adversarial Networks and Improved YOLOv3 Model","publication_year":2020,"publication_date":"2020-08-08","ids":{"openalex":"https://openalex.org/W3048180155","doi":"https://doi.org/10.3390/s20164430","mag":"3048180155","pmid":"https://pubmed.ncbi.nlm.nih.gov/32784403"},"language":"en","primary_location":{"id":"doi:10.3390/s20164430","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20164430","pdf_url":"https://www.mdpi.com/1424-8220/20/16/4430/pdf?version=1596876935","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/16/4430/pdf?version=1596876935","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090964624","display_name":"Ze Luo","orcid":"https://orcid.org/0000-0002-6261-6279"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]},{"id":"https://openalex.org/I96478251","display_name":"Hunan Institute of Technology","ror":"https://ror.org/04n3k2k71","country_code":"CN","type":"education","lineage":["https://openalex.org/I96478251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ze Luo","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Northeast Forestry University, No.26 Hexing Road, Harbin 150040, China","School of Electrical Information Engineering, Hunan Institute of Technology, NO.18 Henghua Road, Hengyang 421010, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Northeast Forestry University, No.26 Hexing Road, Harbin 150040, China","institution_ids":["https://openalex.org/I47689461"]},{"raw_affiliation_string":"School of Electrical Information Engineering, Hunan Institute of Technology, NO.18 Henghua Road, Hengyang 421010, China","institution_ids":["https://openalex.org/I96478251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100953643","display_name":"Huiling Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiling Yu","raw_affiliation_strings":["College of Information and Computer Engineering, Northeast Forestry University, No.26 Hexing Road, Harbin 150040, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Computer Engineering, Northeast Forestry University, No.26 Hexing Road, Harbin 150040, China","institution_ids":["https://openalex.org/I47689461"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101721789","display_name":"Yizhuo Zhang","orcid":"https://orcid.org/0000-0003-3827-5870"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yizhuo Zhang","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Northeast Forestry University, No.26 Hexing Road, Harbin 150040, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Northeast Forestry University, No.26 Hexing Road, Harbin 150040, China","institution_ids":["https://openalex.org/I47689461"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101721789"],"corresponding_institution_ids":["https://openalex.org/I47689461"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":4.162,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.9339114,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"20","issue":"16","first_page":"4430","last_page":"4430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9645000100135803,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6905847191810608},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6863222122192383},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6147050857543945},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5475633144378662},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5147109627723694},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5071446895599365},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4972231686115265},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4866536259651184},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.48397231101989746},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.46262407302856445},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.45274338126182556},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42863065004348755},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4246790111064911},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23497599363327026}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6905847191810608},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6863222122192383},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6147050857543945},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5475633144378662},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5147109627723694},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5071446895599365},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4972231686115265},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4866536259651184},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.48397231101989746},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.46262407302856445},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.45274338126182556},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42863065004348755},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4246790111064911},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23497599363327026},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004784","descriptor_name":"Environmental Monitoring","qualifier_ui":"Q000295","qualifier_name":"instrumentation","is_major_topic":false},{"descriptor_ui":"D004784","descriptor_name":"Environmental Monitoring","qualifier_ui":"Q000295","qualifier_name":"instrumentation","is_major_topic":false},{"descriptor_ui":"D004784","descriptor_name":"Environmental Monitoring","qualifier_ui":"Q000295","qualifier_name":"instrumentation","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","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},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D028223","descriptor_name":"Pinus","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D028223","descriptor_name":"Pinus","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D028223","descriptor_name":"Pinus","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s20164430","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20164430","pdf_url":"https://www.mdpi.com/1424-8220/20/16/4430/pdf?version=1596876935","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:32784403","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32784403","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:67de61e033224c3f9387a23223759236","is_oa":true,"landing_page_url":"https://doaj.org/article/67de61e033224c3f9387a23223759236","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 20, Iss 16, p 4430 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/16/4430/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s20164430","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 20; Issue 16; Pages: 4430","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7472199","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7472199","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20164430","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20164430","pdf_url":"https://www.mdpi.com/1424-8220/20/16/4430/pdf?version=1596876935","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.5799999833106995}],"awards":[{"id":"https://openalex.org/G47954853","display_name":null,"funder_award_id":"2572017CB34","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3048180155.pdf","grobid_xml":"https://content.openalex.org/works/W3048180155.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1563697767","https://openalex.org/W1710476689","https://openalex.org/W2515194294","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2609077090","https://openalex.org/W2746808752","https://openalex.org/W2758007480","https://openalex.org/W2794284562","https://openalex.org/W2794462931","https://openalex.org/W2796347433","https://openalex.org/W2802344799","https://openalex.org/W2804118216","https://openalex.org/W2804860796","https://openalex.org/W2890591987","https://openalex.org/W2910371627","https://openalex.org/W2925449641","https://openalex.org/W2936307272","https://openalex.org/W2944676352","https://openalex.org/W2950628590","https://openalex.org/W2962766617","https://openalex.org/W2963037989","https://openalex.org/W2963446712","https://openalex.org/W2963459241","https://openalex.org/W2970971581","https://openalex.org/W2978896230","https://openalex.org/W2990640894","https://openalex.org/W2997747012","https://openalex.org/W3011886372","https://openalex.org/W6637568146","https://openalex.org/W6750378353","https://openalex.org/W6758744917"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4391584540","https://openalex.org/W2969228573","https://openalex.org/W2963690996","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531"],"abstract_inverted_index":{"The":[0,181,230],"real-time":[1],"detection":[2,48,79,89,118,122,159,231,237],"of":[3,20,26,34,47,53,64,80,113,153,161,168,188,244],"pine":[4,8,21,36,81,87],"cones":[5],"in":[6,55,77,149],"Korean":[7,35],"forests":[9],"is":[10,107,208,239],"not":[11,68],"only":[12],"the":[13,17,27,32,61,78,111,150,158,165,171,186,189,204,211,217,226,236,245],"data":[14,115,138,199],"basis":[15],"for":[16,30,50,198],"mechanized":[18],"picking":[19],"cones,":[22],"but":[23,60],"also":[24],"one":[25],"important":[28],"methods":[29,66],"evaluating":[31],"yield":[33],"forests.":[37],"In":[38,83],"recent":[39],"years,":[40],"there":[41],"has":[42,67],"been":[43,69,75],"a":[44,86,143,178],"certain":[45],"number":[46],"accuracy":[49,232],"image":[51,128],"processing":[52],"fruits":[54],"trees":[56],"using":[57,170,196],"deep-learning":[58],"methods,":[59],"overall":[62],"performance":[63,187],"these":[65],"satisfactory,":[70],"and":[71,99,120,131,163,225,235],"they":[72],"have":[73],"never":[74],"used":[76],"cones.":[82],"this":[84],"paper,":[85],"cone":[88],"method":[90],"based":[91],"on":[92],"Boundary":[93],"Equilibrium":[94],"Generative":[95],"Adversarial":[96],"Networks":[97],"(BEGAN)":[98],"You":[100],"Only":[101],"Look":[102],"Once":[103],"(YOLO)":[104],"v3":[105],"mode":[106],"proposed":[108],"to":[109,136],"solve":[110],"problems":[112],"insufficient":[114],"set,":[116],"inaccurate":[117],"result":[119],"slow":[121],"speed.":[123],"First,":[124],"we":[125,141,156,176],"use":[126],"traditional":[127],"augmentation":[129],"technology":[130],"generative":[132],"adversarial":[133],"network":[134,146,152,222],"BEGAN":[135,197],"implement":[137],"augmentation.":[139,200],"Second,":[140],"introduced":[142],"densely":[144],"connected":[145],"(DenseNet)":[147],"structure":[148],"backbone":[151],"YOLOv3.":[154,247],"Third,":[155],"expanded":[157],"scale":[160],"YOLOv3,":[162],"optimized":[164],"loss":[166],"function":[167],"YOLOv3":[169,206,228],"Distance-IoU":[172],"(DIoU)":[173],"algorithm.":[174],"Finally,":[175],"conducted":[177],"comparative":[179],"experiment.":[180],"experimental":[182],"results":[183],"show":[184],"that":[185,243],"model":[190,207],"can":[191],"be":[192],"effectively":[193],"improved":[194,205],"by":[195],"Under":[201],"same":[202],"conditions,":[203],"better":[209],"than":[210,242],"Single":[212],"Shot":[213],"MultiBox":[214],"Detector":[215],"(SSD),":[216],"faster-regions":[218],"with":[219],"convolutional":[220],"neural":[221],"(Faster":[223],"R-CNN)":[224],"original":[227,246],"model.":[229],"reaches":[233],"95.3%,":[234],"efficiency":[238],"37.8%":[240],"higher":[241]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
