{"id":"https://openalex.org/W3171831022","doi":"https://doi.org/10.3390/rs13122288","title":"Two-Stream Dense Feature Fusion Network Based on RGB-D Data for the Real-Time Prediction of Weed Aboveground Fresh Weight in a Field Environment","display_name":"Two-Stream Dense Feature Fusion Network Based on RGB-D Data for the Real-Time Prediction of Weed Aboveground Fresh Weight in a Field Environment","publication_year":2021,"publication_date":"2021-06-11","ids":{"openalex":"https://openalex.org/W3171831022","doi":"https://doi.org/10.3390/rs13122288","mag":"3171831022"},"language":"en","primary_location":{"id":"doi:10.3390/rs13122288","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13122288","pdf_url":"https://www.mdpi.com/2072-4292/13/12/2288/pdf","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/2072-4292/13/12/2288/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063082187","display_name":"Longzhe Quan","orcid":"https://orcid.org/0000-0002-6391-0365"},"institutions":[{"id":"https://openalex.org/I140221134","display_name":"Anhui Agricultural University","ror":"https://ror.org/0327f3359","country_code":"CN","type":"education","lineage":["https://openalex.org/I140221134"]},{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longzhe Quan","raw_affiliation_strings":["College of Engineering, Anhui Agricultural University, Anhui 230036, China","College of Engineering, Northeast Agricultural University, Harbin 150030, China"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Anhui Agricultural University, Anhui 230036, China","institution_ids":["https://openalex.org/I140221134"]},{"raw_affiliation_string":"College of Engineering, Northeast Agricultural University, Harbin 150030, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013540466","display_name":"Hengda Li","orcid":"https://orcid.org/0000-0001-8067-8871"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengda Li","raw_affiliation_strings":["College of Engineering, Northeast Agricultural University, Harbin 150030, China"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Northeast Agricultural University, Harbin 150030, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440670","display_name":"Hailong Li","orcid":"https://orcid.org/0000-0002-4038-7129"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hailong Li","raw_affiliation_strings":["College of Engineering, Northeast Agricultural University, Harbin 150030, China"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Northeast Agricultural University, Harbin 150030, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100698468","display_name":"Wei Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Jiang","raw_affiliation_strings":["College of Engineering, Northeast Agricultural University, Harbin 150030, China"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Northeast Agricultural University, Harbin 150030, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101863753","display_name":"Zhaoxia Lou","orcid":"https://orcid.org/0000-0002-8209-6186"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoxia Lou","raw_affiliation_strings":["College of Engineering, Northeast Agricultural University, Harbin 150030, China"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Northeast Agricultural University, Harbin 150030, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100717368","display_name":"Liqing Chen","orcid":"https://orcid.org/0000-0003-2482-0866"},"institutions":[{"id":"https://openalex.org/I140221134","display_name":"Anhui Agricultural University","ror":"https://ror.org/0327f3359","country_code":"CN","type":"education","lineage":["https://openalex.org/I140221134"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liqing Chen","raw_affiliation_strings":["College of Engineering, Anhui Agricultural University, Anhui 230036, China"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Anhui Agricultural University, Anhui 230036, China","institution_ids":["https://openalex.org/I140221134"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100717368"],"corresponding_institution_ids":["https://openalex.org/I140221134"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.4326,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.93795807,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"13","issue":"12","first_page":"2288","last_page":"2288"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9994999766349792,"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":0.9994999766349792,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9789000153541565,"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"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9732999801635742,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.8101577758789062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6734213829040527},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6318716406822205},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5795814394950867},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5450627207756042},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5166826248168945},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4393937885761261},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.42596617341041565},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4188120663166046},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4121333956718445},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.33577126264572144},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1694658398628235}],"concepts":[{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.8101577758789062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6734213829040527},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6318716406822205},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5795814394950867},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5450627207756042},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5166826248168945},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4393937885761261},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42596617341041565},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4188120663166046},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4121333956718445},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.33577126264572144},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1694658398628235},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs13122288","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13122288","pdf_url":"https://www.mdpi.com/2072-4292/13/12/2288/pdf","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:3b5c4d3835164da3b623aaa5928433c3","is_oa":true,"landing_page_url":"https://doaj.org/article/3b5c4d3835164da3b623aaa5928433c3","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 13, Iss 12, p 2288 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/13/12/2288/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs13122288","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","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs13122288","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13122288","pdf_url":"https://www.mdpi.com/2072-4292/13/12/2288/pdf","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/2","score":0.7300000190734863,"display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G2082826544","display_name":null,"funder_award_id":"Postdoctoral","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/G2590209832","display_name":null,"funder_award_id":"LBH-Q19007","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/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7242434443","display_name":null,"funder_award_id":"52075092","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3171831022.pdf","grobid_xml":"https://content.openalex.org/works/W3171831022.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1977739898","https://openalex.org/W1980711090","https://openalex.org/W2000261527","https://openalex.org/W2058164160","https://openalex.org/W2061263933","https://openalex.org/W2064341623","https://openalex.org/W2066312471","https://openalex.org/W2073929666","https://openalex.org/W2076063813","https://openalex.org/W2084173010","https://openalex.org/W2091334856","https://openalex.org/W2107051248","https://openalex.org/W2113869211","https://openalex.org/W2127943252","https://openalex.org/W2163922914","https://openalex.org/W2193145675","https://openalex.org/W2254106841","https://openalex.org/W2286091602","https://openalex.org/W2299358847","https://openalex.org/W2491519837","https://openalex.org/W2569479441","https://openalex.org/W2591083172","https://openalex.org/W2618530766","https://openalex.org/W2623225060","https://openalex.org/W2743352521","https://openalex.org/W2743449486","https://openalex.org/W2760986250","https://openalex.org/W2763798658","https://openalex.org/W2767767563","https://openalex.org/W2781967587","https://openalex.org/W2784453654","https://openalex.org/W2804539524","https://openalex.org/W2891950633","https://openalex.org/W2894202761","https://openalex.org/W2899607431","https://openalex.org/W2908783980","https://openalex.org/W2909494862","https://openalex.org/W2913227116","https://openalex.org/W2915011392","https://openalex.org/W2921056216","https://openalex.org/W2939442134","https://openalex.org/W2953476424","https://openalex.org/W2996928306","https://openalex.org/W3008369512","https://openalex.org/W3022353848","https://openalex.org/W3031965526","https://openalex.org/W3047532279","https://openalex.org/W3085500592","https://openalex.org/W3093134863","https://openalex.org/W3106250896","https://openalex.org/W3115519526","https://openalex.org/W3136950817","https://openalex.org/W3162156352","https://openalex.org/W4230080747","https://openalex.org/W4245978153","https://openalex.org/W4251967907","https://openalex.org/W6683994600","https://openalex.org/W6713600794"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W4399188509","https://openalex.org/W4312417841"],"abstract_inverted_index":{"The":[0,101,120,176,196,229,269,285],"aboveground":[1,149],"fresh":[2,45,82,150,299],"weight":[3,46,83,300],"of":[4,26,35,80,84,97,204,217,231,239,248,297],"weeds":[5,41,137],"is":[6,90,118,129,213,235,243,258,266],"an":[7],"important":[8],"indicator":[9],"that":[10,37,200,216],"reflects":[11],"their":[12,44,148],"biomass":[13],"and":[14,17,42,95,107,138,160,174,188,261,304,310],"physiological":[15],"activity":[16],"directly":[18],"affects":[19],"the":[20,24,33,77,81,93,124,132,140,153,189,201,205,211,218,223,226,232,241,245,249,262,294,302],"criteria":[21],"for":[22,51,76,92,115,170,186,280,293],"determining":[23],"amount":[25],"herbicides":[27],"to":[28,130,135,146,165,307],"apply.":[29],"In":[30,59,152],"precision":[31],"agriculture,":[32],"development":[34],"models":[36],"can":[38,47,275,287,305],"accurately":[39],"locate":[40,136],"predict":[43,147],"provide":[48,276,289],"visual":[49,277],"support":[50,279],"accurate,":[52],"variable":[53,282],"herbicide":[54,283],"application":[55],"in":[56,126,181,272,301],"real":[57],"time.":[58],"this":[60,127,273],"work,":[61],"we":[62],"develop":[63],"a":[64,108,167,253,290],"two-stream":[65,141,154],"dense":[66,142,155],"feature":[67,143,156,172],"fusion":[68,144,157],"convolutional":[69,183,206],"network":[70,145,207,219,234],"model":[71,134,251,270,286],"based":[72],"on":[73],"RGB-D":[74,98,209],"data":[75,87,99,105,111,117],"real-time":[78],"prediction":[79,296],"weeds.":[85],"A":[86],"collection":[88],"method":[89,113,292],"developed":[91],"compilation":[94],"production":[96],"sets.":[100],"acquired":[102],"images":[103],"undergo":[104],"enhancement,":[106],"depth":[109,116],"transformation":[110],"enhancement":[112],"suitable":[114],"proposed.":[119],"main":[121],"idea":[122],"behind":[123],"approach":[125],"study":[128],"use":[131,139],"YOLO-V4":[133],"weight.":[151],"network,":[158],"DenseNet":[159],"NiN":[161],"methods":[162],"are":[163],"used":[164],"construct":[166],"Dense-NiN-Block":[168,177,227],"structure":[169],"deep":[171],"extraction":[173],"fusion.":[175],"module":[178],"was":[179],"embedded":[180],"five":[182],"neural":[184],"networks":[185],"comparison,":[187],"best":[190],"results":[191,198],"were":[192],"achieved":[193],"with":[194,252],"DenseNet201.":[195],"test":[197],"show":[199],"predictive":[202],"ability":[203],"using":[208,220],"as":[210,222],"input":[212,224],"better":[214],"than":[215],"RGB":[221],"without":[225],"module.":[228],"mAP":[230],"proposed":[233,271],"75.34%":[236],"(IoU":[237],"value":[238],"0.5),":[240],"IoU":[242],"86.36%,":[244],"detection":[246],"speed":[247],"fastest":[250],"RTX2080Ti":[254],"NVIDIA":[255],"graphics":[256],"card":[257],"17.8":[259],"fps,":[260],"average":[263],"relative":[264],"error":[265],"approximately":[267],"4%.":[268],"paper":[274],"technical":[278],"precise,":[281],"application.":[284],"also":[288],"reference":[291],"non-destructive":[295],"crop":[298,308],"field":[303],"contribute":[306],"breeding":[309],"genetic":[311],"improvement.":[312]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-19T08:26:33.389920","created_date":"2025-10-10T00:00:00"}
