{"id":"https://openalex.org/W3022861781","doi":"https://doi.org/10.3390/rs12091395","title":"A Lightweight Spectral\u2013Spatial Feature Extraction and Fusion Network for Hyperspectral Image Classification","display_name":"A Lightweight Spectral\u2013Spatial Feature Extraction and Fusion Network for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-04-28","ids":{"openalex":"https://openalex.org/W3022861781","doi":"https://doi.org/10.3390/rs12091395","mag":"3022861781"},"language":"en","primary_location":{"id":"doi:10.3390/rs12091395","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12091395","pdf_url":"https://www.mdpi.com/2072-4292/12/9/1395/pdf?version=1588235127","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/2072-4292/12/9/1395/pdf?version=1588235127","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100327248","display_name":"Lin-Lin Chen","orcid":"https://orcid.org/0000-0002-7186-0492"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linlin Chen","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science &amp; Technology, Nanjing 210094, China","Zijin College, Nanjing University of Science &amp; Technology, Nanjing 210023, China"],"raw_orcid":"https://orcid.org/0000-0002-7186-0492","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science &amp; Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"Zijin College, Nanjing University of Science &amp; Technology, Nanjing 210023, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070343691","display_name":"Zhihui Wei","orcid":"https://orcid.org/0000-0002-4841-6051"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhihui Wei","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science &amp; Technology, Nanjing 210094, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science &amp; Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100649896","display_name":"Yang Xu","orcid":"https://orcid.org/0000-0003-3514-9705"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Xu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science &amp; Technology, Nanjing 210094, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science &amp; Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070343691"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.5898,"has_fulltext":true,"cited_by_count":37,"citation_normalized_percentile":{"value":0.95249943,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"12","issue":"9","first_page":"1395","last_page":"1395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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":0.9901000261306763,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9868000149726868,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7717371582984924},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7690557241439819},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.765195369720459},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7141386270523071},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7104752659797668},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5690777897834778},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.523662269115448},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5220396518707275},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4864339828491211},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4554360508918762},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.43580561876296997},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4180077016353607},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34350237250328064},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12005957961082458}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7717371582984924},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7690557241439819},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.765195369720459},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7141386270523071},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7104752659797668},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5690777897834778},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.523662269115448},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5220396518707275},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4864339828491211},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4554360508918762},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.43580561876296997},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4180077016353607},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34350237250328064},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12005957961082458},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12091395","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12091395","pdf_url":"https://www.mdpi.com/2072-4292/12/9/1395/pdf?version=1588235127","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:d5d3f8117f1a4f6c80c45662945fce91","is_oa":true,"landing_page_url":"https://doaj.org/article/d5d3f8117f1a4f6c80c45662945fce91","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":"Remote Sensing, Vol 12, Iss 9, p 1395 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/9/1395/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12091395","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 12; Issue 9; Pages: 1395","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12091395","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12091395","pdf_url":"https://www.mdpi.com/2072-4292/12/9/1395/pdf?version=1588235127","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":[],"awards":[{"id":"https://openalex.org/G1035975025","display_name":null,"funder_award_id":"Grant 2017M611814","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G1164990487","display_name":null,"funder_award_id":"BK20170858","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G1445000783","display_name":null,"funder_award_id":"BK20170858","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1919711014","display_name":null,"funder_award_id":"61772274","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G211540393","display_name":null,"funder_award_id":"BK20180018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2408134068","display_name":null,"funder_award_id":"2017M611814","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G2475309145","display_name":null,"funder_award_id":"61701238","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3059471314","display_name":null,"funder_award_id":"BK20191409","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G4272255732","display_name":null,"funder_award_id":"Grant 61671243","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4586324220","display_name":null,"funder_award_id":"30919011402","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4726786726","display_name":null,"funder_award_id":"30919011234","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5393695307","display_name":null,"funder_award_id":"11431015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5617332474","display_name":null,"funder_award_id":"30919011103","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6756378969","display_name":null,"funder_award_id":"BK20180018","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G7681531949","display_name":null,"funder_award_id":"Grant 61701238","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8256822388","display_name":null,"funder_award_id":"61671243","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8450347332","display_name":null,"funder_award_id":"2018T110502","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G8620067024","display_name":null,"funder_award_id":"30917015104","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G866745652","display_name":null,"funder_award_id":"Grant 11431015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8808510320","display_name":null,"funder_award_id":"Grant 61772274","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3022861781.pdf","grobid_xml":"https://content.openalex.org/works/W3022861781.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W248389711","https://openalex.org/W1521436688","https://openalex.org/W1607307044","https://openalex.org/W1925745898","https://openalex.org/W1950365613","https://openalex.org/W1967866839","https://openalex.org/W1977617632","https://openalex.org/W2004104348","https://openalex.org/W2028721145","https://openalex.org/W2029316659","https://openalex.org/W2059652044","https://openalex.org/W2090424610","https://openalex.org/W2106051978","https://openalex.org/W2135013272","https://openalex.org/W2152057649","https://openalex.org/W2164330327","https://openalex.org/W2169042894","https://openalex.org/W2169535263","https://openalex.org/W2169877324","https://openalex.org/W2257669061","https://openalex.org/W2396056163","https://openalex.org/W2500751094","https://openalex.org/W2546942002","https://openalex.org/W2548340849","https://openalex.org/W2548791488","https://openalex.org/W2550859190","https://openalex.org/W2555840851","https://openalex.org/W2572303978","https://openalex.org/W2577238056","https://openalex.org/W2579874689","https://openalex.org/W2614326984","https://openalex.org/W2764276316","https://openalex.org/W2768309288","https://openalex.org/W2772452219","https://openalex.org/W2793941577","https://openalex.org/W2808098982","https://openalex.org/W2809113079","https://openalex.org/W2809635958","https://openalex.org/W2852622981","https://openalex.org/W2889943009","https://openalex.org/W2896847173","https://openalex.org/W2914331134","https://openalex.org/W2942454403","https://openalex.org/W3100011500","https://openalex.org/W3102274762","https://openalex.org/W3105357426"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W4378510483","https://openalex.org/W4376166922","https://openalex.org/W3026913501","https://openalex.org/W4318954401"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1],"(HSI)":[2],"classification":[3,138,160],"accuracy":[4,161],"has":[5],"been":[6],"greatly":[7],"improved":[8],"by":[9,106],"employing":[10],"deep":[11,23,57,142,170],"learning.":[12],"The":[13,150],"current":[14],"research":[15],"mainly":[16],"focuses":[17],"on":[18,141,144],"how":[19],"to":[20,25,33,46,50,86,94,167],"build":[21],"a":[22,55,158],"network":[24,60,143,155],"improve":[26],"the":[27,43,74,111,127,168],"accuracy.":[28],"However,":[29],"these":[30],"networks":[31],"tend":[32],"be":[34],"more":[35,39],"complex":[36],"and":[37,48,90,99,103],"have":[38],"parameters,":[40],"which":[41,124,172],"makes":[42],"model":[44,62],"difficult":[45],"train":[47],"easy":[49],"overfit.":[51],"Therefore,":[52],"we":[53],"present":[54],"lightweight":[56],"convolutional":[58],"neural":[59],"(CNN)":[61],"called":[63],"S2FEF-CNN.":[64],"In":[65],"this":[66],"model,":[67],"three":[68,119,145],"S2FEF":[69,80],"blocks":[70,120],"are":[71],"used":[72,147],"for":[73,121],"joint":[75],"spectral\u2013spatial":[76],"features":[77,89,105],"extraction.":[78],"Each":[79],"block":[81],"uses":[82],"1D":[83],"spectral":[84,88,102],"convolution":[85,93],"extract":[87,95],"2D":[91],"spatial":[92,96,104],"features,":[97],"respectively,":[98],"then":[100],"fuses":[101],"multiplication.":[107],"Instead":[108],"of":[109],"using":[110],"full":[112],"connected":[113],"layer,":[114],"two":[115],"pooling":[116],"layers":[117],"follow":[118],"dimension":[122],"reduction,":[123],"further":[125],"reduces":[126],"training":[128],"parameters.":[129],"We":[130],"compared":[131,166],"our":[132,154],"method":[133],"with":[134,162],"some":[135],"state-of-the-art":[136],"HSI":[137,178],"methods":[139],"based":[140],"commonly":[146],"hyperspectral":[148],"datasets.":[149],"results":[151],"show":[152],"that":[153],"can":[156],"achieve":[157],"comparable":[159],"significantly":[163],"reduced":[164],"parameters":[165],"above":[169],"networks,":[171],"reflects":[173],"its":[174],"potential":[175],"advantages":[176],"in":[177],"classification.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
