{"id":"https://openalex.org/W3044090999","doi":"https://doi.org/10.1109/tim.2020.3011777","title":"Multiview-Based Random Rotation Ensemble Pruning for Hyperspectral Image Classification","display_name":"Multiview-Based Random Rotation Ensemble Pruning for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-07-24","ids":{"openalex":"https://openalex.org/W3044090999","doi":"https://doi.org/10.1109/tim.2020.3011777","mag":"3044090999"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.3011777","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3011777","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/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"]},{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Youqiang Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103152696","display_name":"Guo Cao","orcid":"https://orcid.org/0000-0003-4386-8136"},"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"],"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/A5025442255","display_name":"Xuesong Li","orcid":"https://orcid.org/0000-0002-2370-8998"},"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"],"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":3,"corresponding_author_ids":["https://openalex.org/A5062745950"],"corresponding_institution_ids":["https://openalex.org/I36399199","https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":2.6411,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.91691234,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"70","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":0.9998000264167786,"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":0.9998000264167786,"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/T12676","display_name":"Machine Learning and ELM","score":0.9986000061035156,"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/T10057","display_name":"Face and Expression Recognition","score":0.9836999773979187,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7318726778030396},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.6935949325561523},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6725671291351318},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6635560989379883},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6524996757507324},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6213250756263733},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5866010189056396},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5393149852752686},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5264352560043335},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4842076301574707},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.4839909076690674},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.444215327501297},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4328690767288208},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3228382468223572},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22497466206550598},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1667889654636383}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7318726778030396},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.6935949325561523},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6725671291351318},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6635560989379883},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6524996757507324},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6213250756263733},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5866010189056396},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5393149852752686},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5264352560043335},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4842076301574707},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.4839909076690674},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.444215327501297},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4328690767288208},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3228382468223572},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22497466206550598},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1667889654636383}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2020.3011777","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3011777","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4847742897","display_name":null,"funder_award_id":"BK20191284","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G7666350340","display_name":null,"funder_award_id":"61371168","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7776482482","display_name":null,"funder_award_id":"61801222","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/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1534477342","https://openalex.org/W1972524915","https://openalex.org/W1974861955","https://openalex.org/W1988790447","https://openalex.org/W1999663947","https://openalex.org/W2004754531","https://openalex.org/W2008997808","https://openalex.org/W2025328644","https://openalex.org/W2029316659","https://openalex.org/W2032483883","https://openalex.org/W2036389990","https://openalex.org/W2052160904","https://openalex.org/W2059477850","https://openalex.org/W2090424610","https://openalex.org/W2092590148","https://openalex.org/W2096553553","https://openalex.org/W2097238823","https://openalex.org/W2097915756","https://openalex.org/W2100128988","https://openalex.org/W2101711129","https://openalex.org/W2111072639","https://openalex.org/W2113242816","https://openalex.org/W2118206198","https://openalex.org/W2118463106","https://openalex.org/W2130627644","https://openalex.org/W2136251662","https://openalex.org/W2144439732","https://openalex.org/W2146096861","https://openalex.org/W2150757437","https://openalex.org/W2152057649","https://openalex.org/W2160356822","https://openalex.org/W2161211851","https://openalex.org/W2166163522","https://openalex.org/W2168880067","https://openalex.org/W2289977264","https://openalex.org/W2302010255","https://openalex.org/W2317602876","https://openalex.org/W2518897583","https://openalex.org/W2595902385","https://openalex.org/W2603422184","https://openalex.org/W2617818785","https://openalex.org/W2725960771","https://openalex.org/W2753290709","https://openalex.org/W2764276316","https://openalex.org/W2789643644","https://openalex.org/W2794091565","https://openalex.org/W2901819993","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W2914309864","https://openalex.org/W2945989246","https://openalex.org/W2946655868","https://openalex.org/W2952921651","https://openalex.org/W2954914461","https://openalex.org/W2987422477","https://openalex.org/W3010411193","https://openalex.org/W4212883601","https://openalex.org/W6632075054","https://openalex.org/W6698146022"],"related_works":["https://openalex.org/W1981866886","https://openalex.org/W2052615004","https://openalex.org/W2046975922","https://openalex.org/W3009797526","https://openalex.org/W4361733484","https://openalex.org/W4256395896","https://openalex.org/W2057416691","https://openalex.org/W1760344465","https://openalex.org/W4205397888","https://openalex.org/W2770076983"],"abstract_inverted_index":{"Ensembles":[0],"of":[1,22,76,102,183,191],"extreme":[2],"learning":[3,24],"machine":[4],"(ELM)":[5],"have":[6,17,125],"been":[7],"widely":[8],"used":[9,168],"for":[10,137],"hyperspectral":[11,202],"image":[12],"classification.":[13],"The":[14,54],"previous":[15],"studies":[16],"shown":[18],"that":[19,73,164,208],"the":[20,35,74,82,85,117,122,139,147,165,181,184,189,192,213],"goal":[21],"ensemble":[23,52,62,132,159,172,185],"is":[25,105,135],"to":[26,33,48,71,107,156,169],"train":[27],"accurate":[28,175],"but":[29,176],"diverse":[30],"component":[31,118,140,149,166],"classifiers":[32,119,141,150,167],"improve":[34],"generalization":[36],"performance.":[37],"To":[38,187],"approach":[39,101],"this":[40,42],"goal,":[41],"article":[43],"proposes":[44],"a":[45,99,157],"novel":[46,68],"framework":[47,56],"construct":[49,158,170],"an":[50,129,171],"ELM":[51],"model.":[53],"proposed":[55,193,214],"relies":[57],"on":[58,121,200],"multiview-based":[59],"random":[60,97],"rotation":[61],"pruning":[63,133,138],"(MVRR-EP)":[64],"and":[65,145],"has":[66],"several":[67],"features.":[69],"First,":[70],"ensure":[72],"subsets":[75],"spectral":[77,86],"bands":[78,87],"can":[79],"sufficiently":[80],"learn":[81],"target":[83],"concept,":[84],"are":[88,154,174],"divided":[89],"into":[90,111],"multiviews":[91],"by":[92],"using":[93],"correlation":[94],"analysis.":[95],"Second,":[96],"rotation,":[98],"new":[100],"space":[103],"transformation,":[104],"introduced":[106],"transform":[108],"each":[109],"view":[110],"multiple":[112],"coordinate":[113],"spaces,":[114],"which":[115,178],"makes":[116],"trained":[120],"transformed":[123],"spaces":[124],"great":[126],"diversity.":[127],"Third,":[128],"accuracy":[130],"guided":[131],"strategy":[134],"designed":[136],"with":[142,151,210],"low":[143],"complementarity,":[144],"consequently,":[146],"remaining":[148],"high":[152],"complementarity":[153],"combined":[155],"classifier.":[160,186],"These":[161],"techniques":[162],"guarantee":[163],"classifier":[173],"diverse,":[177],"ultimately":[179],"improves":[180],"performance":[182],"demonstrate":[188],"effectiveness":[190],"MVRR-EP,":[194],"extensive":[195],"experiments":[196],"were":[197],"carried":[198],"out":[199],"four":[201],"data":[203],"sets.":[204],"Experimental":[205],"results":[206],"verify":[207],"compared":[209],"other":[211],"methods,":[212],"method":[215],"provides":[216],"competitive":[217],"results.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}