{"id":"https://openalex.org/W3097090744","doi":"https://doi.org/10.3390/rs12213547","title":"Full Convolutional Neural Network Based on Multi-Scale Feature Fusion for the Class Imbalance Remote Sensing Image Classification","display_name":"Full Convolutional Neural Network Based on Multi-Scale Feature Fusion for the Class Imbalance Remote Sensing Image Classification","publication_year":2020,"publication_date":"2020-10-29","ids":{"openalex":"https://openalex.org/W3097090744","doi":"https://doi.org/10.3390/rs12213547","mag":"3097090744"},"language":"en","primary_location":{"id":"doi:10.3390/rs12213547","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12213547","pdf_url":"https://www.mdpi.com/2072-4292/12/21/3547/pdf?version=1604029530","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/2072-4292/12/21/3547/pdf?version=1604029530","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101938260","display_name":"Yuanyuan Ren","orcid":"https://orcid.org/0009-0003-0918-2939"},"institutions":[{"id":"https://openalex.org/I102208913","display_name":"Shihezi University","ror":"https://ror.org/04x0kvm78","country_code":"CN","type":"education","lineage":["https://openalex.org/I102208913"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Ren","raw_affiliation_strings":["School of Information Science and Technology, Shihezi University, Shihezi 832000, China","Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Shihezi University, Shihezi 832000, China","institution_ids":["https://openalex.org/I102208913"]},{"raw_affiliation_string":"Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016709118","display_name":"Xianfeng Zhang","orcid":"https://orcid.org/0000-0002-2475-4558"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianfeng Zhang","raw_affiliation_strings":["Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China","Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China"],"raw_orcid":"https://orcid.org/0000-0002-2475-4558","affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I20231570"]},{"raw_affiliation_string":"Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101019549","display_name":"Yongjian Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I102208913","display_name":"Shihezi University","ror":"https://ror.org/04x0kvm78","country_code":"CN","type":"education","lineage":["https://openalex.org/I102208913"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjian Ma","raw_affiliation_strings":["School of Information Science and Technology, Shihezi University, Shihezi 832000, China","Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Shihezi University, Shihezi 832000, China","institution_ids":["https://openalex.org/I102208913"]},{"raw_affiliation_string":"Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056351649","display_name":"Qiyuan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I102208913","display_name":"Shihezi University","ror":"https://ror.org/04x0kvm78","country_code":"CN","type":"education","lineage":["https://openalex.org/I102208913"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiyuan Yang","raw_affiliation_strings":["School of Information Science and Technology, Shihezi University, Shihezi 832000, China","Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Shihezi University, Shihezi 832000, China","institution_ids":["https://openalex.org/I102208913"]},{"raw_affiliation_string":"Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033048932","display_name":"Chuanjian Wang","orcid":"https://orcid.org/0000-0002-4340-1002"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chuanjian Wang","raw_affiliation_strings":["School of Internet, Anhui University, Hefei 230039, China","Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Internet, Anhui University, Hefei 230039, China","institution_ids":["https://openalex.org/I143868143"]},{"raw_affiliation_string":"Xinjiang Corps Branch of National Remote Sensing Center, Shihezi 832000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100606438","display_name":"Hailong Liu","orcid":"https://orcid.org/0000-0001-9853-9327"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hailong Liu","raw_affiliation_strings":["School of Resources and Environment, University of Electronic Science and Technology of China, Chendu 611731, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Resources and Environment, University of Electronic Science and Technology of China, Chendu 611731, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083815488","display_name":"Quan Qi","orcid":"https://orcid.org/0000-0003-3088-6319"},"institutions":[{"id":"https://openalex.org/I102208913","display_name":"Shihezi University","ror":"https://ror.org/04x0kvm78","country_code":"CN","type":"education","lineage":["https://openalex.org/I102208913"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Qi","raw_affiliation_strings":["School of Information Science and Technology, Shihezi University, Shihezi 832000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Shihezi University, Shihezi 832000, China","institution_ids":["https://openalex.org/I102208913"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5033048932"],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":5.1636,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.95893295,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"12","issue":"21","first_page":"3547","last_page":"3547"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"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":0.9995999932289124,"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/T11659","display_name":"Advanced Image Fusion Techniques","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/T13282","display_name":"Automated Road and Building Extraction","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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":0.7627971172332764},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5962435007095337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5811050534248352},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5575888752937317},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5386677980422974},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4818626344203949},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.47472748160362244},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4746200144290924},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.4594297409057617},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4521007537841797},{"id":"https://openalex.org/keywords/cohens-kappa","display_name":"Cohen's kappa","score":0.44321632385253906},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4261007308959961},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4190792739391327},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1838158369064331},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11784884333610535},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.11482447385787964}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7627971172332764},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5962435007095337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5811050534248352},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5575888752937317},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5386677980422974},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4818626344203949},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.47472748160362244},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4746200144290924},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.4594297409057617},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4521007537841797},{"id":"https://openalex.org/C163864269","wikidata":"https://www.wikidata.org/wiki/Q1107106","display_name":"Cohen's kappa","level":2,"score":0.44321632385253906},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4261007308959961},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4190792739391327},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1838158369064331},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11784884333610535},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.11482447385787964},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12213547","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12213547","pdf_url":"https://www.mdpi.com/2072-4292/12/21/3547/pdf?version=1604029530","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:a404e4fdbfe7409b90f6044334125dc1","is_oa":true,"landing_page_url":"https://doaj.org/article/a404e4fdbfe7409b90f6044334125dc1","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 21, p 3547 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/21/3547/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12213547","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/rs12213547","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12213547","pdf_url":"https://www.mdpi.com/2072-4292/12/21/3547/pdf?version=1604029530","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W1949049686","https://openalex.org/W2029185882","https://openalex.org/W2051636611","https://openalex.org/W2053724458","https://openalex.org/W2085625911","https://openalex.org/W2098676252","https://openalex.org/W2104978738","https://openalex.org/W2108598243","https://openalex.org/W2109255472","https://openalex.org/W2138776277","https://openalex.org/W2162915993","https://openalex.org/W2261059368","https://openalex.org/W2267317359","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2595964094","https://openalex.org/W2623913549","https://openalex.org/W2737129951","https://openalex.org/W2756201869","https://openalex.org/W2760340275","https://openalex.org/W2771038928","https://openalex.org/W2791784608","https://openalex.org/W2792542990","https://openalex.org/W2793853538","https://openalex.org/W2804860796","https://openalex.org/W2887035499","https://openalex.org/W2894561647","https://openalex.org/W2902055884","https://openalex.org/W2915254566","https://openalex.org/W2919115771","https://openalex.org/W2922021721","https://openalex.org/W2931239307","https://openalex.org/W2939660331","https://openalex.org/W2950925862","https://openalex.org/W2963881378","https://openalex.org/W2964217532","https://openalex.org/W2964309882","https://openalex.org/W2968570763","https://openalex.org/W2991488782","https://openalex.org/W2991616716","https://openalex.org/W2992240579","https://openalex.org/W2995783349","https://openalex.org/W2999178925","https://openalex.org/W3000627240","https://openalex.org/W3004822919","https://openalex.org/W3017059353","https://openalex.org/W3017568635","https://openalex.org/W3018254460","https://openalex.org/W3038606102","https://openalex.org/W3100449589","https://openalex.org/W3100521496","https://openalex.org/W3117585232","https://openalex.org/W4250482878","https://openalex.org/W6787734735","https://openalex.org/W7020680850"],"related_works":["https://openalex.org/W2348909947","https://openalex.org/W4292672442","https://openalex.org/W2362101859","https://openalex.org/W2791431590","https://openalex.org/W2941610985","https://openalex.org/W4235810826","https://openalex.org/W3000105423","https://openalex.org/W2350688482","https://openalex.org/W2964954556","https://openalex.org/W3088721469"],"abstract_inverted_index":{"Remote":[0],"sensing":[1,19,95,144],"image":[2,20,59,117],"segmentation":[3],"with":[4,64,81],"samples":[5,87],"imbalance":[6,66,183],"is":[7,119],"always":[8],"one":[9],"of":[10,24,48,86,141,156],"the":[11,22,69,98,129,138,157,161,172,186,198],"most":[12],"important":[13],"issues.":[14],"Typically,":[15],"a":[16,114,192],"high-resolution":[17,142],"remote":[18,94,143],"has":[21],"characteristics":[23],"high":[25],"spatial":[26,151],"resolution":[27],"and":[28,45,62,171,185],"low":[29],"spectral":[30,139],"resolution,":[31],"complex":[32],"large-scale":[33],"land":[34,41],"covers,":[35,42],"small":[36],"class":[37],"differences":[38],"for":[39],"some":[40],"vague":[43],"foreground,":[44],"imbalanced":[46],"distribution":[47],"samples.":[49],"However,":[50],"traditional":[51],"machine":[52],"learning":[53],"algorithms":[54],"have":[55],"limitations":[56],"in":[57,197],"deep":[58],"feature":[60],"extraction":[61],"dealing":[63],"sample":[65,182],"issue.":[67],"In":[68,89],"paper,":[70],"we":[71,91],"proposed":[72,158],"an":[73],"improved":[74,130],"full-convolution":[75],"neural":[76],"network,":[77],"called":[78],"DeepLab":[79,131],"V3+,":[80],"loss":[82],"function":[83],"based":[84],"solution":[85],"imbalance.":[88],"addition,":[90],"select":[92],"Sentinel-2":[93],"images":[96],"covering":[97],"Yuli":[99],"County,":[100],"Bayingolin":[101],"Mongol":[102],"Autonomous":[103,107],"Prefecture,":[104],"Xinjiang":[105],"Uygur":[106],"Region,":[108],"China":[109],"as":[110],"data":[111,122,188],"sources,":[112],"then":[113],"typical":[115],"region":[116],"dataset":[118,163],"built":[120],"by":[121],"augmentation.":[123],"The":[124,153,166,176],"experimental":[125],"results":[126],"show":[127],"that":[128],"V3+":[132],"model":[133],"can":[134,190],"not":[135],"only":[136],"utilize":[137],"information":[140],"images,":[145],"but":[146],"also":[147],"consider":[148],"its":[149],"rich":[150],"information.":[152],"classification":[154],"accuracy":[155],"method":[159],"on":[160],"test":[162],"reaches":[164,169],"97.97%.":[165],"mean":[167],"Intersection-over-Union":[168],"87.74%,":[170],"Kappa":[173],"coefficient":[174],"0.9587.":[175],"work":[177],"provides":[178],"methodological":[179],"guidance":[180],"to":[181,194],"correction,":[184],"established":[187],"resource":[189],"be":[191],"reference":[193],"further":[195],"study":[196],"future.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
