{"id":"https://openalex.org/W4390603854","doi":"https://doi.org/10.1109/tgrs.2024.3350055","title":"Channel-Layer-Oriented Lightweight Spectral\u2013Spatial Network for Hyperspectral Image Classification","display_name":"Channel-Layer-Oriented Lightweight Spectral\u2013Spatial Network for Hyperspectral Image Classification","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4390603854","doi":"https://doi.org/10.1109/tgrs.2024.3350055"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3350055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3350055","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069094590","display_name":"Chunchao Li","orcid":"https://orcid.org/0000-0003-0878-6733"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunchao Li","raw_affiliation_strings":["College of Computer Science and Technology and the State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology and the State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042657950","display_name":"Behnood Rasti","orcid":"https://orcid.org/0000-0002-1091-9841"},"institutions":[{"id":"https://openalex.org/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Behnood Rasti","raw_affiliation_strings":["Machine Learning Group, Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany"],"affiliations":[{"raw_affiliation_string":"Machine Learning Group, Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany","institution_ids":["https://openalex.org/I4210148560","https://openalex.org/I2801798921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053099673","display_name":"Xuebin Tang","orcid":"https://orcid.org/0000-0001-5144-7943"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuebin Tang","raw_affiliation_strings":["College of Computer Science and Technology and the State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology and the State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011401698","display_name":"Puhong Duan","orcid":"https://orcid.org/0000-0001-5066-4399"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Puhong Duan","raw_affiliation_strings":["College of Electrical and Information Engineering and the Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering and the Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361659","display_name":"Jun Li","orcid":"https://orcid.org/0000-0001-7055-7873"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043043084","display_name":"Yuanxi Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanxi Peng","raw_affiliation_strings":["College of Computer Science and Technology and the State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology and the State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5069094590"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":16.0417,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.99322708,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"14"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.977400004863739,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7938417196273804},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7832965850830078},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5541919469833374},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5184707045555115},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5177658796310425},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5056278705596924},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.488757848739624},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4656648635864258},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.46076393127441406},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.4594815969467163},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.45228856801986694},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4468315541744232},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.42962217330932617},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38913455605506897},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34459012746810913},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.310219943523407}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7938417196273804},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7832965850830078},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5541919469833374},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5184707045555115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5177658796310425},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5056278705596924},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.488757848739624},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4656648635864258},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.46076393127441406},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.4594815969467163},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.45228856801986694},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4468315541744232},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42962217330932617},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38913455605506897},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34459012746810913},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.310219943523407},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3350055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3350055","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G121302408","display_name":null,"funder_award_id":"91948303-1","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2426787987","display_name":null,"funder_award_id":"MMC202306","funder_id":"https://openalex.org/F4320321435","funder_display_name":"Anhui University"},{"id":"https://openalex.org/G4298695922","display_name":null,"funder_award_id":"2022M721106","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G4998861757","display_name":null,"funder_award_id":"62101575","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5921931442","display_name":null,"funder_award_id":"62371185","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7393014967","display_name":null,"funder_award_id":"2023RC3124","funder_id":"https://openalex.org/F4320330206","funder_display_name":"Science and Technology Program of Hunan Province"},{"id":"https://openalex.org/G7502056569","display_name":null,"funder_award_id":"2023T160208","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G8759851568","display_name":null,"funder_award_id":"62201207","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G885265327","display_name":null,"funder_award_id":"62106278","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/F4320321435","display_name":"Anhui University","ror":"https://ror.org/05th6yx34"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320330206","display_name":"Science and Technology Program of Hunan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W2475283175","https://openalex.org/W2500751094","https://openalex.org/W2531409750","https://openalex.org/W2609880332","https://openalex.org/W2752782242","https://openalex.org/W2883780447","https://openalex.org/W2889861425","https://openalex.org/W2904698365","https://openalex.org/W2914331134","https://openalex.org/W2941387379","https://openalex.org/W2942454403","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2982083293","https://openalex.org/W3003552243","https://openalex.org/W3022592629","https://openalex.org/W3024007459","https://openalex.org/W3031696400","https://openalex.org/W3035414587","https://openalex.org/W3044657819","https://openalex.org/W3046027728","https://openalex.org/W3047443805","https://openalex.org/W3049655825","https://openalex.org/W3103695279","https://openalex.org/W3114720220","https://openalex.org/W3120356488","https://openalex.org/W3122028341","https://openalex.org/W3122774149","https://openalex.org/W3122817280","https://openalex.org/W3123961948","https://openalex.org/W3145183637","https://openalex.org/W3167109952","https://openalex.org/W3167649504","https://openalex.org/W3184654054","https://openalex.org/W3190492058","https://openalex.org/W3206052460","https://openalex.org/W3214821343","https://openalex.org/W3217526930","https://openalex.org/W4200482478","https://openalex.org/W4205722319","https://openalex.org/W4210794570","https://openalex.org/W4220853886","https://openalex.org/W4226428166","https://openalex.org/W4226467560","https://openalex.org/W4280563105","https://openalex.org/W4285214186","https://openalex.org/W4293812296","https://openalex.org/W4295308436","https://openalex.org/W4297775537","https://openalex.org/W4312513332","https://openalex.org/W4313524854","https://openalex.org/W4313644075","https://openalex.org/W4323338300","https://openalex.org/W4362690177","https://openalex.org/W4364323060","https://openalex.org/W4366493021","https://openalex.org/W4367320924","https://openalex.org/W4382203304","https://openalex.org/W4383113435","https://openalex.org/W4385325854","https://openalex.org/W4386047745","https://openalex.org/W4386076695","https://openalex.org/W4386918729","https://openalex.org/W4388440484","https://openalex.org/W4388624513","https://openalex.org/W6737664043","https://openalex.org/W6762718338"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1],"(HSI)":[2],"classification":[3,165,183],"is":[4,123,172],"commonly":[5],"influenced":[6],"by":[7,51,125,212],"convolution":[8,91,98],"neural":[9],"networks":[10],"(CNNs).":[11],"However,":[12],"the":[13,72,117,126,139,144,156],"large":[14,57],"number":[15],"of":[16,119,158],"parameters":[17],"and":[18,32,59,137,161,190,203],"computational":[19],"complexity":[20],"associated":[21],"with":[22,96,129,194],"CNNs":[23,160],"can":[24],"limit":[25],"their":[26],"practical":[27],"application,":[28],"particularly":[29],"when":[30],"computing":[31],"storage":[33],"resources":[34],"are":[35,221],"limited.":[36],"To":[37],"address":[38],"this":[39],"challenge,":[40],"we":[41,63,78,108,152],"propose":[42,109],"a":[43,80,87,110,120,176],"channel-layer-oriented":[44],"lightweight":[45,191],"network":[46,171,199],"for":[47],"HSI":[48,164],"classification.":[49],"Motivated":[50],"existing":[52],"structures":[53],"that":[54,92,133],"typically":[55],"set":[56],"channels":[58],"stack":[60],"multiple":[61],"layers,":[62],"give":[64],"more":[65],"optimal":[66],"solutions":[67],"strategically":[68],"to":[69,99,154,174],"further":[70],"compress":[71],"model.":[73],"For":[74,104],"intralayer":[75],"feature":[76],"extraction,":[77],"develop":[79],"channel-oriented":[81],"spectral\u2013spatial":[82,102],"module":[83],"(COS2M),":[84],"which":[85],"introduces":[86],"dual-single-channel":[88],"(DSC)":[89],"3-D":[90],"works":[93],"in":[94],"conjunction":[95],"depthwise":[97],"fully":[100],"extract":[101],"information.":[103],"interlayer":[105],"information":[106,135],"transmission,":[107],"novel":[111],"neighbor-pixel-aware":[112],"activation":[113,118,146],"function":[114],"(NPAF),":[115],"where":[116],"single":[121,145],"pixel":[122],"determined":[124],"learnable":[127],"interaction":[128],"its":[130],"neighbor":[131],"range":[132],"enhances":[134],"transmission":[136],"improves":[138],"network\u2019s":[140],"fitting":[141],"ability":[142],"through":[143],"layer.":[147],"By":[148],"implementing":[149],"these":[150],"strategies,":[151],"aim":[153],"overcome":[155],"limitations":[157],"traditional":[159],"enable":[162],"efficient":[163],"within":[166],"resource-constrained":[167],"environments.":[168],"The":[169,198,218],"whole":[170],"designed":[173],"be":[175],"compact":[177],"end-to-end":[178],"structure.":[179],"It":[180],"achieves":[181],"better":[182],"performance":[184],"than":[185],"other":[186],"deep":[187],"learning":[188],"methods":[189],"models,":[192],"even":[193],"limited":[195],"training":[196],"samples.":[197],"parameters,":[200],"model":[201],"complexity,":[202],"inference":[204],"time":[205],"also":[206],"demonstrate":[207],"significant":[208],"superiority,":[209],"as":[210],"confirmed":[211],"experiments":[213],"on":[214],"three":[215],"benchmark":[216],"datasets.":[217],"source":[219],"codes":[220],"available":[222],"publicly":[223],"at:":[224],"<uri":[225],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[226],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/AchunLee/CLOLN_TGRS</uri>":[227]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":36},{"year":2024,"cited_by_count":8}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}