{"id":"https://openalex.org/W2790275230","doi":"https://doi.org/10.1109/jstars.2018.2809781","title":"Cascaded Random Forest for Hyperspectral Image Classification","display_name":"Cascaded Random Forest for Hyperspectral Image Classification","publication_year":2018,"publication_date":"2018-03-16","ids":{"openalex":"https://openalex.org/W2790275230","doi":"https://doi.org/10.1109/jstars.2018.2809781","mag":"2790275230"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2018.2809781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2809781","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5062745950","display_name":"Youqiang Zhang","orcid":"https://orcid.org/0000-0002-4761-4726"},"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":"Youqiang Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4761-4726","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081711485","display_name":"Guo Cao","orcid":null},"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":"Guo Cao","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-2689-0932","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100449087","display_name":"Xuesong Li","orcid":"https://orcid.org/0000-0002-2794-8390"},"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":"Xuesong Li","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024654155","display_name":"Bisheng Wang","orcid":null},"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":"Bisheng Wang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":null,"fwci":7.6623,"has_fulltext":false,"cited_by_count":143,"citation_normalized_percentile":{"value":0.97392202,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"11","issue":"4","first_page":"1082","last_page":"1094"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9987999796867371,"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":0.9987999796867371,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9898999929428101,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/random-forest","display_name":"Random forest","score":0.9025312066078186},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7736219763755798},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7708110213279724},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6853786706924438},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6704420447349548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6276149153709412},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5953117609024048},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.5862573385238647},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5356603860855103},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5341910719871521},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5093322992324829},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.44521480798721313},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.43185022473335266},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4233621060848236},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.31146717071533203},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19957733154296875}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.9025312066078186},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7736219763755798},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7708110213279724},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6853786706924438},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6704420447349548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6276149153709412},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5953117609024048},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.5862573385238647},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5356603860855103},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5341910719871521},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5093322992324829},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.44521480798721313},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.43185022473335266},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4233621060848236},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31146717071533203},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19957733154296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstars.2018.2809781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2809781","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G7666350340","display_name":"\u57fa\u4e8e\u53d8\u5206\u4e0e\u6761\u4ef6\u968f\u673a\u573a\u6a21\u578b\u7684\u9ad8\u5206\u8fa8\u7387\u9065\u611f\u5f71\u50cf\u707e\u5bb3\u635f\u5931\u5b9e\u7269\u91cf\u8bc4\u4f30\u7814\u7a76","funder_award_id":"61371168","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W33911032","https://openalex.org/W986585644","https://openalex.org/W1509786997","https://openalex.org/W1554190159","https://openalex.org/W1594031697","https://openalex.org/W1702637483","https://openalex.org/W1976152398","https://openalex.org/W1980547211","https://openalex.org/W1982621055","https://openalex.org/W1985414995","https://openalex.org/W1988790447","https://openalex.org/W1989919782","https://openalex.org/W1996061706","https://openalex.org/W1998979050","https://openalex.org/W2001014393","https://openalex.org/W2023441160","https://openalex.org/W2043175314","https://openalex.org/W2059056443","https://openalex.org/W2082609813","https://openalex.org/W2093045504","https://openalex.org/W2099206930","https://openalex.org/W2101711129","https://openalex.org/W2113242816","https://openalex.org/W2130627644","https://openalex.org/W2134987394","https://openalex.org/W2145862305","https://openalex.org/W2155632266","https://openalex.org/W2158633287","https://openalex.org/W2167277498","https://openalex.org/W2167397429","https://openalex.org/W2167753478","https://openalex.org/W2192578595","https://openalex.org/W2249336288","https://openalex.org/W2261059368","https://openalex.org/W2273278181","https://openalex.org/W2313466110","https://openalex.org/W2517850251","https://openalex.org/W2518301555","https://openalex.org/W2518421866","https://openalex.org/W2518897583","https://openalex.org/W2533302542","https://openalex.org/W2547846938","https://openalex.org/W2567850567","https://openalex.org/W2570194385","https://openalex.org/W2589780155","https://openalex.org/W2696801991","https://openalex.org/W2725960771","https://openalex.org/W2736577301","https://openalex.org/W2742622811","https://openalex.org/W2744320608","https://openalex.org/W2747189523","https://openalex.org/W2754847445","https://openalex.org/W2757242159","https://openalex.org/W2904955533","https://openalex.org/W2911964244","https://openalex.org/W2912707296","https://openalex.org/W4255833381","https://openalex.org/W6625648380","https://openalex.org/W6680028700"],"related_works":["https://openalex.org/W2393964553","https://openalex.org/W3046032433","https://openalex.org/W2073883415","https://openalex.org/W2089304832","https://openalex.org/W1976812808","https://openalex.org/W2086720713","https://openalex.org/W2014852328","https://openalex.org/W3128011703","https://openalex.org/W2004617984","https://openalex.org/W4390143830"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,34],"Cascaded":[4],"Random":[5,24,40],"Forest":[6,25],"(CRF)":[7],"method,":[8,139],"which":[9,48],"can":[10,49,163],"improve":[11,50],"the":[12,23,31,51,58,64,69,78,81,86,102,109,123,135],"classification":[13],"performance":[14,136],"by":[15],"means":[16],"of":[17,53,63,80,88,137],"combining":[18],"two":[19,62],"different":[20],"enhancements":[21],"into":[22,75],"(RF)":[26],"algorithm.":[27],"In":[28],"detail,":[29],"on":[30,68,152],"one":[32,115],"hand,":[33,71],"neighborhood":[35],"rough":[36],"sets":[37],"based":[38],"Hierarchical":[39],"Subspace":[41],"Method":[42],"is":[43,73,118,141],"designed":[44],"for":[45,84,167],"feature":[46],"selection,":[47],"strength":[52],"base":[54,65,116,128],"classifiers":[55,129],"and":[56,67,148,157],"increase":[57],"diversity":[59],"between":[60],"each":[61,121,131],"classifiers;":[66],"other":[70,144],"Boosting":[72,91,111],"introduced":[74],"RF.":[76],"As":[77],"minimization":[79],"training":[82],"error":[83,99],"updating":[85],"weights":[87,104],"samples":[89],"in":[90,105],"often":[92],"leads":[93],"to":[94,100],"overfitting,":[95],"we":[96],"added":[97],"out-of-bag":[98],"update":[101],"sample":[103],"CRF.":[106],"Different":[107],"from":[108],"existing":[110],"strategy":[112],"that":[113,161],"only":[114],"classifier":[117],"generated":[119],"at":[120,130],"iteration,":[122],"proposed":[124],"CRF":[125,140,162],"trains":[126],"several":[127],"iteration.":[132],"To":[133],"evaluate":[134],"our":[138],"compared":[142],"with":[143],"related":[145],"RF":[146],"methods":[147],"support":[149],"vector":[150],"machine":[151],"three":[153],"benchmark":[154],"hyperspectral":[155,168],"datasets,":[156],"experimental":[158],"results":[159],"show":[160],"provide":[164],"competitive":[165],"solutions":[166],"image":[169],"classification.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":18},{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":4}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2025-10-10T00:00:00"}