{"id":"https://openalex.org/W4388430596","doi":"https://doi.org/10.1109/tgrs.2023.3330568","title":"Hypothesis Margin-Based Ensemble Method for the Classification of Noisy Remote Sensing Data","display_name":"Hypothesis Margin-Based Ensemble Method for the Classification of Noisy Remote Sensing Data","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388430596","doi":"https://doi.org/10.1109/tgrs.2023.3330568"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3330568","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3330568","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/A5068336830","display_name":"Wei Feng","orcid":"https://orcid.org/0000-0003-1907-2664"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"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":true,"raw_author_name":"Wei Feng","raw_affiliation_strings":["Department of Remote Sensing Science and Technology, School of Electronic Engineering, Xidian University, Xi’an, China","Ministry of Education, Key Laboratory of Collaborative Intelligence Systems, Xidian University, Xi'an, China","Xi'an Key Laboratory of Advanced Remote Sensing, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-1907-2664","affiliations":[{"raw_affiliation_string":"Department of Remote Sensing Science and Technology, School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Collaborative Intelligence Systems, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xi'an Key Laboratory of Advanced Remote Sensing, Xi'an, China","institution_ids":["https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066040845","display_name":"Xinting Gao","orcid":"https://orcid.org/0009-0004-1487-9391"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"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":"Xinting Gao","raw_affiliation_strings":["Department of Remote Sensing Science and Technology, School of Electronic Engineering, Xidian University, Xi’an, China","Xi'an Key Laboratory of Advanced Remote Sensing, Xi'an, China","Ministry of Education, Key Laboratory of Collaborative Intelligence Systems, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Remote Sensing Science and Technology, School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xi'an Key Laboratory of Advanced Remote Sensing, Xi'an, China","institution_ids":["https://openalex.org/I4210166112"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Collaborative Intelligence Systems, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042936748","display_name":"Samia Boukir","orcid":"https://orcid.org/0000-0002-0907-081X"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4210166017","display_name":"Institut de Math\u00e9matiques de Bordeaux","ror":"https://ror.org/05m3r1b84","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I15057530","https://openalex.org/I4210141950","https://openalex.org/I4210160189","https://openalex.org/I4210166017"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Samia Boukir","raw_affiliation_strings":["CNRS, Bordeaux Institute of Technology (Bordeaux INP), IMB, UMR 5251, University of Bordeaux, Talence, France"],"raw_orcid":"https://orcid.org/0000-0002-0907-081X","affiliations":[{"raw_affiliation_string":"CNRS, Bordeaux Institute of Technology (Bordeaux INP), IMB, UMR 5251, University of Bordeaux, Talence, France","institution_ids":["https://openalex.org/I4210166017","https://openalex.org/I15057530","https://openalex.org/I4210160189","https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079432209","display_name":"Zhiwei Xie","orcid":"https://orcid.org/0000-0002-2913-9183"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"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":"Zhiwei Xie","raw_affiliation_strings":["Department of Remote Sensing Science and Technology, School of Electronic Engineering, Xidian University, Xi’an, China","Ministry of Education, Key Laboratory of Collaborative Intelligence Systems, Xidian University, Xi'an, China","Xi'an Key Laboratory of Advanced Remote Sensing, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Remote Sensing Science and Technology, School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Collaborative Intelligence Systems, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xi'an Key Laboratory of Advanced Remote Sensing, Xi'an, China","institution_ids":["https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008256662","display_name":"Yinghui Quan","orcid":"https://orcid.org/0000-0001-6541-9441"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"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":"Yinghui Quan","raw_affiliation_strings":["Department of Remote Sensing Science and Technology, School of Electronic Engineering, Xidian University, Xi’an, China","Ministry of Education, Key Laboratory of Collaborative Intelligence Systems, Xidian University, Xi'an, China","Xi'an Key Laboratory of Advanced Remote Sensing, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0001-6541-9441","affiliations":[{"raw_affiliation_string":"Department of Remote Sensing Science and Technology, School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Collaborative Intelligence Systems, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xi'an Key Laboratory of Advanced Remote Sensing, Xi'an, China","institution_ids":["https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109619264","display_name":"Wenjiang Huang","orcid":"https://orcid.org/0009-0009-3343-7034"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjiang Huang","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","Aerospace Information Research Institute, Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Aerospace Information Research Institute, Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021408538","display_name":"Mengdao Xing","orcid":"https://orcid.org/0000-0002-4084-0915"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengdao Xing","raw_affiliation_strings":["Academy of Advanced Interdisciplinary Research, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-4084-0915","affiliations":[{"raw_affiliation_string":"Academy of Advanced Interdisciplinary Research, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5068336830"],"corresponding_institution_ids":["https://openalex.org/I149594827","https://openalex.org/I4210166112"],"apc_list":null,"apc_paid":null,"fwci":1.0225,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81609592,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9950000047683716,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8219019174575806},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.658953070640564},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6430213451385498},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6230597496032715},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6009007692337036},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5758745074272156},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5696263313293457},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5445341467857361},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.543806254863739},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48205575346946716},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47805434465408325},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4304479956626892},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3933263123035431}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8219019174575806},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.658953070640564},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6430213451385498},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6230597496032715},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6009007692337036},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5758745074272156},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5696263313293457},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5445341467857361},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.543806254863739},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48205575346946716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47805434465408325},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4304479956626892},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3933263123035431},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3330568","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3330568","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/G2497081596","display_name":null,"funder_award_id":"2021JC-23","funder_id":"https://openalex.org/F4320336567","funder_display_name":"Natural Science Basic Research Program of Shaanxi Province"},{"id":"https://openalex.org/G2990865709","display_name":null,"funder_award_id":"SXLK2022-02-8","funder_id":"https://openalex.org/F4320335802","funder_display_name":"Shaanxi Key Science and Technology Innovation Team Project"},{"id":"https://openalex.org/G5807194875","display_name":null,"funder_award_id":"12005169","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G620763321","display_name":null,"funder_award_id":"62331019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6419395077","display_name":null,"funder_award_id":"62201438","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/F4320335802","display_name":"Shaanxi Key Science and Technology Innovation Team Project","ror":null},{"id":"https://openalex.org/F4320336567","display_name":"Natural Science Basic Research Program of Shaanxi Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W22120349","https://openalex.org/W1496447628","https://openalex.org/W1594031697","https://openalex.org/W1596345407","https://openalex.org/W1666942233","https://openalex.org/W1975846642","https://openalex.org/W1988790447","https://openalex.org/W1990653740","https://openalex.org/W1996061706","https://openalex.org/W1997731668","https://openalex.org/W1998979050","https://openalex.org/W2008463764","https://openalex.org/W2011287807","https://openalex.org/W2012243161","https://openalex.org/W2016484971","https://openalex.org/W2028925694","https://openalex.org/W2034841618","https://openalex.org/W2050389646","https://openalex.org/W2122111042","https://openalex.org/W2132424470","https://openalex.org/W2136132422","https://openalex.org/W2151973236","https://openalex.org/W2163921091","https://openalex.org/W2167460663","https://openalex.org/W2168809519","https://openalex.org/W2176159905","https://openalex.org/W2194775991","https://openalex.org/W2261059368","https://openalex.org/W2531168480","https://openalex.org/W2799870441","https://openalex.org/W2895410835","https://openalex.org/W2911964244","https://openalex.org/W2954857880","https://openalex.org/W2962770389","https://openalex.org/W2963125010","https://openalex.org/W2982887038","https://openalex.org/W2985365109","https://openalex.org/W2997048423","https://openalex.org/W3004732066","https://openalex.org/W3046705914","https://openalex.org/W3083246299","https://openalex.org/W3098388691","https://openalex.org/W3116272467","https://openalex.org/W3120740533","https://openalex.org/W3120745352","https://openalex.org/W3160553908","https://openalex.org/W4212883601","https://openalex.org/W4232478844","https://openalex.org/W6633899822","https://openalex.org/W6676769703","https://openalex.org/W6684191040","https://openalex.org/W6762718338"],"related_works":["https://openalex.org/W2073883415","https://openalex.org/W2166537673","https://openalex.org/W2905156999","https://openalex.org/W4229460275","https://openalex.org/W4296079469","https://openalex.org/W2944292463","https://openalex.org/W1987518466","https://openalex.org/W3014252901","https://openalex.org/W3135046080","https://openalex.org/W3023033471"],"abstract_inverted_index":{"The":[0,87,169,182],"accuracy":[1],"of":[2,72,90,98,171,179,185],"a":[3,32,38,103,132],"classifier,":[4],"whether":[5],"it":[6],"is":[7,12,28,68,131,174,195,205,239],"an":[8,116],"ensemble":[9,50,64,117,257],"or":[10,56,110],"not,":[11],"directly":[13],"influenced":[14],"by":[15,47,197],"the":[16,44,49,58,70,95,99,225,229,255],"training":[17,25,60,113],"data":[18,26,40,81,84,114,150],"used":[19],"in":[20,115,176],"learning.":[21],"In":[22],"remote":[23,156],"sensing,":[24],"mislabeling":[27,45,165],"inevitable":[29],"and":[30,76,108,166,192,228,252,254],"faces":[31],"major":[33,88,187],"challenge.":[34],"This":[35,145,233],"paper":[36],"proposes":[37],"versatile":[39],"cleaning":[41,151],"which":[42,160],"handles":[43],"problem":[46],"exploiting":[48],"concepts":[51],"for":[52,142,155],"identifying,":[53],"then":[54],"eliminating":[55],"correcting":[57],"mislabeled":[59,80,112],"data.":[61],"A":[62,202],"powerful":[63],"method,":[65],"random":[66,210],"forest,":[67,211],"at":[69],"core":[71],"our":[73,125,149,172,237],"filter":[74],"design":[75,133],"helps":[77],"to":[78,106,128,139,209],"distinguish":[79],"from":[82,163],"uncorrupted":[83],"more":[85,240],"accurately.":[86],"contribution":[89],"this":[91],"work":[92],"lies":[93],"on":[94],"explicit":[96],"use":[97],"hypothesis":[100],"margin":[101],"as":[102,216,218],"decision":[104],"means":[105],"identify":[107],"eliminate":[109],"correct":[111],"learning":[118],"framework.":[119],"Another":[120],"key":[121],"development":[122],"that":[123,134,236],"makes":[124,148],"algorithm":[126,173],"superior":[127],"existing":[129],"approaches":[130],"avoids":[135],"rare":[136],"class":[137,143,199,222],"instances":[138],"be":[140],"mistaken":[141],"noise.":[144],"fundamental":[146],"aspect":[147],"system":[152],"particularly":[153],"suitable":[154],"sensing":[157],"classification":[158],"tasks":[159],"usually":[161],"suffer":[162],"both":[164],"imbalance":[167],"problems.":[168],"effectiveness":[170],"demonstrated":[175],"performing":[177],"mapping":[178],"land":[180],"covers.":[181],"generalization":[183],"performance":[184],"two":[186,219],"supervised":[188],"noise-sensitive":[189],"classifiers,":[190],"boosting":[191],"K-nearest":[193],"neighbors,":[194],"strengthened":[196],"effective":[198],"noise":[200,223],"reduction.":[201],"comparative":[203],"analysis":[204,234],"conducted":[206],"with":[207],"respect":[208],"deep":[212,243],"convolutional":[213,244],"neural":[214,245],"networks,":[215],"well":[217],"well-established":[220],"ensemble-based":[221],"filters,":[224],"majority":[226],"vote":[227,231],"consensus":[230],"filters.":[232],"demonstrates":[235],"approach":[238],"accurate":[241],"than":[242],"networks":[246],"(one-dimensional":[247],"CNN,":[248],"AlexNet,":[249],"EfficientNet,":[250],"ResNet50":[251],"ShuffletNet)":[253],"reference":[256],"methods.":[258]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}