{"id":"https://openalex.org/W3133477028","doi":"https://doi.org/10.1109/jstars.2021.3060769","title":"A Deep Learning Method of Water Body Extraction From High Resolution Remote Sensing Images With Multisensors","display_name":"A Deep Learning Method of Water Body Extraction From High Resolution Remote Sensing Images With Multisensors","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3133477028","doi":"https://doi.org/10.1109/jstars.2021.3060769","mag":"3133477028"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2021.3060769","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2021.3060769","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9314330/09360447.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/9314330/09360447.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100683217","display_name":"Mengya Li","orcid":"https://orcid.org/0000-0001-6712-1868"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengya Li","raw_affiliation_strings":["School of Resources and Environmental Engineering, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-6712-1868","affiliations":[{"raw_affiliation_string":"School of Resources and Environmental Engineering, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065644909","display_name":"Penghai Wu","orcid":"https://orcid.org/0000-0002-1983-5978"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Penghai Wu","raw_affiliation_strings":["School of Resources and Environmental Engineering, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-1983-5978","affiliations":[{"raw_affiliation_string":"School of Resources and Environmental Engineering, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088351292","display_name":"Biao Wang","orcid":"https://orcid.org/0000-0002-3594-7953"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao Wang","raw_affiliation_strings":["School of Resources and Environmental Engineering, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-3594-7953","affiliations":[{"raw_affiliation_string":"School of Resources and Environmental Engineering, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080895438","display_name":"Honglyun Park","orcid":"https://orcid.org/0000-0002-0599-0205"},"institutions":[{"id":"https://openalex.org/I24714338","display_name":"Youngsan University","ror":"https://ror.org/01s5kvh23","country_code":"KR","type":"education","lineage":["https://openalex.org/I24714338"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Honglyun Park","raw_affiliation_strings":["Drone & Transportation Engineering, Youngsan University, Yangsan, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Drone & Transportation Engineering, Youngsan University, Yangsan, South Korea","institution_ids":["https://openalex.org/I24714338"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101436329","display_name":"Hui Yang","orcid":"https://orcid.org/0000-0002-6701-6766"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Hui","raw_affiliation_strings":["Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Anhui, China"],"raw_orcid":"https://orcid.org/0000-0002-6701-6766","affiliations":[{"raw_affiliation_string":"Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Anhui, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100458040","display_name":"Yanlan Wu","orcid":"https://orcid.org/0000-0002-8983-3150"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu Yanlan","raw_affiliation_strings":["Information Materials and Intelligent Sensing Laboratory of Anhui Province Hefei, Anhui, China","Anhui Engineering Research Center for Geographical Information Intelligent Technology, Hefei, China","School of Resources and Environmental Engineering, Anhui University, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Materials and Intelligent Sensing Laboratory of Anhui Province Hefei, Anhui, China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"Anhui Engineering Research Center for Geographical Information Intelligent Technology, Hefei, China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"School of Resources and Environmental Engineering, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":8.5768,"has_fulltext":true,"cited_by_count":110,"citation_normalized_percentile":{"value":0.98381417,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"14","issue":null,"first_page":"3120","last_page":"3132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9919999837875366,"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/T10577","display_name":"Hydrology and Sediment Transport Processes","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7867303490638733},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6939316987991333},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6542156934738159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5930307507514954},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5850439667701721},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5625879168510437},{"id":"https://openalex.org/keywords/water-body","display_name":"Water body","score":0.5099490880966187},{"id":"https://openalex.org/keywords/remote-sensing-application","display_name":"Remote sensing application","score":0.4622611105442047},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4475814998149872},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4392201900482178},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3922806978225708},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18078798055648804},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.1283959448337555},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1280117630958557},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.08502617478370667},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07926419377326965}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7867303490638733},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6939316987991333},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6542156934738159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5930307507514954},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5850439667701721},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5625879168510437},{"id":"https://openalex.org/C2986309107","wikidata":"https://www.wikidata.org/wiki/Q15324","display_name":"Water body","level":2,"score":0.5099490880966187},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.4622611105442047},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4475814998149872},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4392201900482178},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3922806978225708},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18078798055648804},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.1283959448337555},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1280117630958557},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.08502617478370667},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07926419377326965},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2021.3060769","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2021.3060769","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9314330/09360447.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d8d86ed32fd64fdeafb217c0f0eacd85","is_oa":true,"landing_page_url":"https://doaj.org/article/d8d86ed32fd64fdeafb217c0f0eacd85","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":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 3120-3132 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2021.3060769","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2021.3060769","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9314330/09360447.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Clean water and sanitation","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/6"}],"awards":[{"id":"https://openalex.org/G1436692991","display_name":null,"funder_award_id":"2008085QD188","funder_id":"https://openalex.org/F4320334897","funder_display_name":"Natural Science Foundation of Anhui Province"},{"id":"https://openalex.org/G5092423305","display_name":null,"funder_award_id":"41901282","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6648801017","display_name":"\u652f\u6301\u591a\u7279\u5f81\u6574\u5408\u89c6\u89c9\u6ce8\u610f\u673a\u5236\u7684\u503e\u659c\u6444\u5f71\u70b9\u4e91\u5206\u7c7b\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5","funder_award_id":"41971311","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7315664857","display_name":null,"funder_award_id":"2008085QD188","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/F4320334897","display_name":"Natural Science Foundation of Anhui Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3133477028.pdf","grobid_xml":"https://content.openalex.org/works/W3133477028.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W36401000","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1982206826","https://openalex.org/W2007300776","https://openalex.org/W2018349799","https://openalex.org/W2022811154","https://openalex.org/W2077509829","https://openalex.org/W2091362016","https://openalex.org/W2098676252","https://openalex.org/W2101439532","https://openalex.org/W2101678239","https://openalex.org/W2149298154","https://openalex.org/W2294123605","https://openalex.org/W2336807904","https://openalex.org/W2383884902","https://openalex.org/W2412782625","https://openalex.org/W2603731349","https://openalex.org/W2616755213","https://openalex.org/W2749751926","https://openalex.org/W2764034829","https://openalex.org/W2767581044","https://openalex.org/W2782522152","https://openalex.org/W2783165089","https://openalex.org/W2793682472","https://openalex.org/W2802942478","https://openalex.org/W2896720583","https://openalex.org/W2899362480","https://openalex.org/W2903468154","https://openalex.org/W2940726923","https://openalex.org/W2951841689","https://openalex.org/W2963446712","https://openalex.org/W2963859992","https://openalex.org/W2963881378","https://openalex.org/W2964121744","https://openalex.org/W2968084579","https://openalex.org/W2995487320","https://openalex.org/W3005739096","https://openalex.org/W3015281476","https://openalex.org/W3086575992","https://openalex.org/W4238100585","https://openalex.org/W6601502559","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6639824700","https://openalex.org/W6675245165","https://openalex.org/W6756686628","https://openalex.org/W6771709999","https://openalex.org/W6783573070","https://openalex.org/W7038629539"],"related_works":["https://openalex.org/W3000097931","https://openalex.org/W2354322770","https://openalex.org/W4237547500","https://openalex.org/W1570848052","https://openalex.org/W2373192430","https://openalex.org/W4239268388","https://openalex.org/W1537496349","https://openalex.org/W4243305035","https://openalex.org/W2379407973","https://openalex.org/W2185710839"],"abstract_inverted_index":{"Water":[0],"body":[1,56,150,162,191,211],"extraction":[2,192,212],"from":[3,23,57,151,213],"remote":[4,24,59,143,153,168,183,215],"sensing":[5,25,60,144,154,169,184,216],"images":[6,61,145,217],"is":[7,95,113],"an":[8],"important":[9],"task.":[10],"Deep":[11],"learning":[12],"has":[13],"become":[14],"a":[15,34,44,159],"more":[16,122],"popular":[17],"method":[18,193],"for":[19,141],"extracting":[20,54],"water":[21,55,149,161,190,210],"bodies":[22],"images.":[26,155,170,185],"However,":[27],"these":[28],"methods":[29],"are":[30,38],"usually":[31],"aimed":[32],"at":[33,53],"specific":[35],"sensor":[36],"and":[37,138,181,194,219],"not":[39],"applicable.":[40],"Thus,":[41],"we":[42,133,157],"proposed":[43,172],"new":[45,160],"network,":[46,65],"called":[47],"the":[48,69,73,82,92,104,121,127,131,136,142,188,197,206],"dense-local-feature-compression":[49],"(DLFC)":[50],"network":[51,70],"aiming":[52],"different":[58,105,152],"automatic.":[62],"In":[63],"this":[64],"each":[66],"layer":[67],"of":[68,76,86,107],"can":[71,102,119,134,147,208],"receive":[72],"feature":[74,93],"maps":[75],"all":[77],"layers":[78],"before":[79,115],"it":[80],"by":[81,126],"densely":[83],"connected":[84],"module":[85,112],"DenseNet.":[87],"The":[88,110,171,202],"concatenate":[89,116],"operation":[90],"on":[91,165],"dimension":[94],"used":[96],"when":[97],"connecting":[98],"across":[99],"layers.":[100],"It":[101,118],"realize":[103,209],"levels":[106],"features":[108,124],"reuse.":[109],"local-feature-compression":[111],"introduced":[114],"operation.":[117,129],"obtain":[120],"abstract":[123],"further":[125],"convolution":[128],"Through":[130],"DLFC,":[132],"fuse":[135],"spatial":[137],"spectral":[139],"information":[140],"that":[146,205],"extract":[148],"Besides,":[156],"construct":[158],"dataset":[163],"based":[164],"GaoFen-2":[166],"(GF-2)":[167],"DLFC":[173,198,207],"achieved":[174],"excellent":[175],"performance":[176],"with":[177,187],"GF-2,":[178],"GaoFen-6,":[179],"Sentinel-2,":[180],"ZY-3":[182],"Compared":[186],"traditional":[189],"contemporary":[195],"networks,":[196],"exhibits":[199],"noticeable":[200],"improvement.":[201],"results":[203],"indicate":[204],"multisource":[214],"automatically":[218],"rapidly.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
