{"id":"https://openalex.org/W2943214363","doi":"https://doi.org/10.3390/rs11091006","title":"Integrating Multitemporal Sentinel-1/2 Data for Coastal Land Cover Classification Using a Multibranch Convolutional Neural Network: A Case of the Yellow River Delta","display_name":"Integrating Multitemporal Sentinel-1/2 Data for Coastal Land Cover Classification Using a Multibranch Convolutional Neural Network: A Case of the Yellow River Delta","publication_year":2019,"publication_date":"2019-04-28","ids":{"openalex":"https://openalex.org/W2943214363","doi":"https://doi.org/10.3390/rs11091006","mag":"2943214363"},"language":"en","primary_location":{"id":"doi:10.3390/rs11091006","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11091006","pdf_url":"https://www.mdpi.com/2072-4292/11/9/1006/pdf?version=1556501246","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/11/9/1006/pdf?version=1556501246","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078340301","display_name":"Quanlong Feng","orcid":"https://orcid.org/0000-0002-0569-4131"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quanlong Feng","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China","College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China"],"affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106406865","display_name":"Jianyu Yang","orcid":"https://orcid.org/0009-0002-8660-8254"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianyu Yang","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100837014","display_name":"Dehai Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dehai Zhu","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101450769","display_name":"Jiantao Liu","orcid":"https://orcid.org/0000-0001-5836-5641"},"institutions":[{"id":"https://openalex.org/I44445938","display_name":"Shandong Jianzhu University","ror":"https://ror.org/01gbfax37","country_code":"CN","type":"education","lineage":["https://openalex.org/I44445938"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiantao Liu","raw_affiliation_strings":["School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China"],"affiliations":[{"raw_affiliation_string":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China","institution_ids":["https://openalex.org/I44445938"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037921908","display_name":"Hao Guo","orcid":"https://orcid.org/0000-0001-9317-4015"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Guo","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016271984","display_name":"Bayartungalag Batsaikhan","orcid":"https://orcid.org/0000-0002-4296-4225"},"institutions":[{"id":"https://openalex.org/I144917393","display_name":"Mongolian University of Science and Technology","ror":"https://ror.org/02shmve39","country_code":"MN","type":"education","lineage":["https://openalex.org/I144917393"]}],"countries":["MN"],"is_corresponding":false,"raw_author_name":"Batsaikhan Bayartungalag","raw_affiliation_strings":["Research Center for Ecology and Sustainable Development, Mongolian University of Science and Technology, Ulaanbaatar 14191, Mongolia"],"affiliations":[{"raw_affiliation_string":"Research Center for Ecology and Sustainable Development, Mongolian University of Science and Technology, Ulaanbaatar 14191, Mongolia","institution_ids":["https://openalex.org/I144917393"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100758249","display_name":"Baoguo Li","orcid":"https://orcid.org/0000-0002-9847-2449"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoguo Li","raw_affiliation_strings":["College of Land Science and Technology, China Agricultural University, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5106406865"],"corresponding_institution_ids":["https://openalex.org/I52158045"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":10.6971,"has_fulltext":false,"cited_by_count":98,"citation_normalized_percentile":{"value":0.98398728,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"11","issue":"9","first_page":"1006","last_page":"1006"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10341","display_name":"Coral and Marine Ecosystems Studies","score":0.9778000116348267,"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":0.6866003274917603},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.6830675601959229},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6514581441879272},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6401155591011047},{"id":"https://openalex.org/keywords/cohens-kappa","display_name":"Cohen's kappa","score":0.6058028936386108},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.46543943881988525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43418365716934204},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4298360049724579},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4278908967971802},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4136839509010315},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37417078018188477},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33596885204315186},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.29347607493400574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2435566782951355},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10782378911972046}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6866003274917603},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.6830675601959229},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6514581441879272},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6401155591011047},{"id":"https://openalex.org/C163864269","wikidata":"https://www.wikidata.org/wiki/Q1107106","display_name":"Cohen's kappa","level":2,"score":0.6058028936386108},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.46543943881988525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43418365716934204},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4298360049724579},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4278908967971802},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4136839509010315},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37417078018188477},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33596885204315186},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.29347607493400574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2435566782951355},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10782378911972046},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"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":3,"locations":[{"id":"doi:10.3390/rs11091006","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11091006","pdf_url":"https://www.mdpi.com/2072-4292/11/9/1006/pdf?version=1556501246","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:38aacf305c30493ab8c8f249482d4b2c","is_oa":true,"landing_page_url":"https://doaj.org/article/38aacf305c30493ab8c8f249482d4b2c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 11, Iss 9, p 1006 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/11/9/1006/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs11091006","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":"Remote Sensing; Volume 11; Issue 9; Pages: 1006","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs11091006","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11091006","pdf_url":"https://www.mdpi.com/2072-4292/11/9/1006/pdf?version=1556501246","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","display_name":"Life below water","score":0.7900000214576721}],"awards":[{"id":"https://openalex.org/G6429229455","display_name":null,"funder_award_id":"2018M641529","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2943214363.pdf","grobid_xml":"https://content.openalex.org/works/W2943214363.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W1496628205","https://openalex.org/W1528268891","https://openalex.org/W1537604559","https://openalex.org/W1677182931","https://openalex.org/W1970323848","https://openalex.org/W1974567844","https://openalex.org/W1984667420","https://openalex.org/W1988353925","https://openalex.org/W1994780096","https://openalex.org/W2010806274","https://openalex.org/W2017555282","https://openalex.org/W2032338257","https://openalex.org/W2060879964","https://openalex.org/W2072587793","https://openalex.org/W2111626609","https://openalex.org/W2138499468","https://openalex.org/W2158001550","https://openalex.org/W2163605009","https://openalex.org/W2212980623","https://openalex.org/W2336879049","https://openalex.org/W2548679149","https://openalex.org/W2565258258","https://openalex.org/W2601564443","https://openalex.org/W2618530766","https://openalex.org/W2760923572","https://openalex.org/W2764034829","https://openalex.org/W2765739551","https://openalex.org/W2771249998","https://openalex.org/W2772365113","https://openalex.org/W2773793494","https://openalex.org/W2776305546","https://openalex.org/W2778936354","https://openalex.org/W2782522152","https://openalex.org/W2783608381","https://openalex.org/W2786038065","https://openalex.org/W2799924016","https://openalex.org/W2803946774","https://openalex.org/W2811244448","https://openalex.org/W2883925605","https://openalex.org/W2884821113","https://openalex.org/W2895854890","https://openalex.org/W2898910301","https://openalex.org/W2900420505","https://openalex.org/W2907459272","https://openalex.org/W2908968031","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W2951392520","https://openalex.org/W2963351448","https://openalex.org/W2964121744","https://openalex.org/W3102288316","https://openalex.org/W3104839310","https://openalex.org/W6631190155","https://openalex.org/W6658567143","https://openalex.org/W6736170873","https://openalex.org/W6743731764"],"related_works":["https://openalex.org/W3000097931","https://openalex.org/W2442738406","https://openalex.org/W4390240101","https://openalex.org/W4377014260","https://openalex.org/W4245827621","https://openalex.org/W2541496036","https://openalex.org/W4306942285","https://openalex.org/W1989870285","https://openalex.org/W2747202660","https://openalex.org/W2357530009"],"abstract_inverted_index":{"Coastal":[0],"land":[1,76,105,141,225],"cover":[2,77,106,142,226],"classification":[3,36,78,107,227],"is":[4],"a":[5,56,87,113,125,161],"significant":[6],"yet":[7],"challenging":[8],"task":[9],"in":[10,48,59,191],"remote":[11,29,63],"sensing":[12,30],"because":[13],"of":[14,20,25,41,62,96,115,158,164,167,175,183],"the":[15,60,94,148,187,203,209],"complex":[16],"and":[17,27,52,69,98,160,215,218],"fragmented":[18],"nature":[19],"coastal":[21,75,104,224],"landscapes.":[22],"However,":[23],"availability":[24],"multitemporal":[26,97,168,217],"multisensor":[28,99,178],"data":[31,101,169,179],"provides":[32],"opportunities":[33],"to":[34,102,120,138,181],"improve":[35,103],"accuracy.":[37,108,228],"Meanwhile,":[38],"rapid":[39],"development":[40],"deep":[42,71],"learning":[43,72],"has":[44,53],"achieved":[45],"astonishing":[46],"results":[47,145],"computer":[49],"vision":[50],"tasks":[51],"also":[54,194],"been":[55],"popular":[57],"topic":[58],"field":[61],"sensing.":[64],"Nevertheless,":[65],"designing":[66],"an":[67,133,155,173],"effective":[68],"concise":[70],"model":[73,111],"for":[74,93],"remains":[79],"problematic.":[80],"To":[81],"tackle":[82],"this":[83,192],"issue,":[84],"we":[85],"propose":[86],"multibranch":[88],"convolutional":[89,117],"neural":[90,118],"network":[91],"(MBCNN)":[92],"fusion":[95,136,189],"Sentinel":[100,220],"The":[109],"proposed":[110,149,210],"leverages":[112],"series":[114],"deformable":[116],"networks":[119],"extract":[121],"representative":[122],"features":[123,129],"from":[124],"single-source":[126],"dataset.":[127],"Extracted":[128],"are":[130],"aggregated":[131],"through":[132],"adaptive":[134],"feature":[135],"module":[137,190],"predict":[139],"final":[140],"categories.":[143],"Experimental":[144],"indicate":[146],"that":[147,208],"MBCNN":[150],"shows":[151],"good":[152],"performance,":[153],"with":[154,202],"overall":[156],"accuracy":[157,171,184,196],"93.78%":[159],"Kappa":[162],"coefficient":[163],"0.9297.":[165],"Inclusion":[166],"improves":[170,223],"by":[172,197],"average":[174],"6.85%,":[176],"while":[177],"contributes":[180],"3.24%":[182],"increase.":[185],"Additionally,":[186],"featured":[188],"study":[193],"increases":[195],"about":[198],"2%":[199],"when":[200],"compared":[201],"feature-stacking":[204],"method.":[205],"Results":[206],"demonstrate":[207],"method":[211],"can":[212],"effectively":[213],"mine":[214],"fuse":[216],"multisource":[219],"data,":[221],"which":[222]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":5}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2019-05-09T00:00:00"}