{"id":"https://openalex.org/W2757242159","doi":"https://doi.org/10.1109/tgrs.2017.2744662","title":"Random Forest Ensembles and Extended Multiextinction Profiles for Hyperspectral Image Classification","display_name":"Random Forest Ensembles and Extended Multiextinction Profiles for Hyperspectral Image Classification","publication_year":2017,"publication_date":"2017-09-19","ids":{"openalex":"https://openalex.org/W2757242159","doi":"https://doi.org/10.1109/tgrs.2017.2744662","mag":"2757242159"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2017.2744662","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2017.2744662","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/A5000395252","display_name":"Junshi Xia","orcid":"https://orcid.org/0000-0002-5586-6536"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Junshi Xia","raw_affiliation_strings":["Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5586-6536","affiliations":[{"raw_affiliation_string":"Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074919292","display_name":"Pedram Ghamisi","orcid":"https://orcid.org/0000-0003-1203-741X"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]},{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Pedram Ghamisi","raw_affiliation_strings":["Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Wessling, Germany","Signal Processing in Earth Observation, Technische Universitat Munchen, Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0003-1203-741X","affiliations":[{"raw_affiliation_string":"Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Wessling, Germany","institution_ids":["https://openalex.org/I2898391981"]},{"raw_affiliation_string":"Signal Processing in Earth Observation, Technische Universitat Munchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034435383","display_name":"Naoto Yokoya","orcid":"https://orcid.org/0000-0002-7321-4590"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoto Yokoya","raw_affiliation_strings":["Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-7321-4590","affiliations":[{"raw_affiliation_string":"Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005014399","display_name":"Akira Iwasaki","orcid":"https://orcid.org/0000-0002-1603-8041"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Iwasaki","raw_affiliation_strings":["Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":11.5733,"has_fulltext":false,"cited_by_count":200,"citation_normalized_percentile":{"value":0.98453699,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"56","issue":"1","first_page":"202","last_page":"216"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9796000123023987,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.9086837768554688},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8768560886383057},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6816334128379822},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6759070754051208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6699934601783752},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6653491854667664},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6035653948783875},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5362880229949951},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5309426784515381},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.5018355846405029},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4249507188796997},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.418844997882843},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2871286869049072},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24466919898986816},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07247719168663025}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.9086837768554688},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8768560886383057},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6816334128379822},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6759070754051208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6699934601783752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6653491854667664},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6035653948783875},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5362880229949951},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5309426784515381},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.5018355846405029},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4249507188796997},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.418844997882843},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2871286869049072},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24466919898986816},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07247719168663025},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2017.2744662","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2017.2744662","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"},{"id":"pmh:oai:elib.dlr.de:115365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/TGRS.2017.2744662>.","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Zeitschriftenbeitrag"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G62103250","display_name":"On board processing of Hyperspectral Data","funder_award_id":"16H04587","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8086252123","display_name":"Multidimensional high-resolution remote sensing based on spectral data fusion","funder_award_id":"15K20955","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8216977332","display_name":"\u30a2\u30f3\u30b5\u30f3\u30d6\u30eb\u5b66\u7fd2\u306b\u3088\u308b\u591a\u7a2e\u30ea\u30e2\u30fc\u30c8\u30bb\u30f3\u30b7\u30f3\u30b0\u30c7\u30fc\u30bf\u306e\u753b\u50cf\u5206\u985e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3068\u5fdc\u7528","funder_award_id":"16F16053","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W110443002","https://openalex.org/W229472839","https://openalex.org/W1141500385","https://openalex.org/W1532610010","https://openalex.org/W1556668337","https://openalex.org/W1561442812","https://openalex.org/W2001298023","https://openalex.org/W2004553299","https://openalex.org/W2004754531","https://openalex.org/W2011287807","https://openalex.org/W2053852479","https://openalex.org/W2062964394","https://openalex.org/W2064886835","https://openalex.org/W2083541351","https://openalex.org/W2098057602","https://openalex.org/W2101711129","https://openalex.org/W2104269704","https://openalex.org/W2106277226","https://openalex.org/W2107285841","https://openalex.org/W2108597246","https://openalex.org/W2112076978","https://openalex.org/W2113242816","https://openalex.org/W2114220616","https://openalex.org/W2115451191","https://openalex.org/W2115629999","https://openalex.org/W2123649031","https://openalex.org/W2124868070","https://openalex.org/W2127199143","https://openalex.org/W2130627644","https://openalex.org/W2131864940","https://openalex.org/W2133277699","https://openalex.org/W2136251662","https://openalex.org/W2143516773","https://openalex.org/W2146842130","https://openalex.org/W2149471024","https://openalex.org/W2150757437","https://openalex.org/W2154506590","https://openalex.org/W2156909104","https://openalex.org/W2157691228","https://openalex.org/W2158400785","https://openalex.org/W2159070926","https://openalex.org/W2160662337","https://openalex.org/W2167114860","https://openalex.org/W2212636544","https://openalex.org/W2295766016","https://openalex.org/W2346557146","https://openalex.org/W2487087946","https://openalex.org/W2500751094","https://openalex.org/W2506684654","https://openalex.org/W2516282711","https://openalex.org/W2519956323","https://openalex.org/W2531168480","https://openalex.org/W2570194385","https://openalex.org/W2900032653","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W3135396862","https://openalex.org/W4212883601","https://openalex.org/W6633275910","https://openalex.org/W6676769703","https://openalex.org/W6679984647","https://openalex.org/W6756024327"],"related_works":["https://openalex.org/W2375684291","https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W2354676191","https://openalex.org/W2044184146","https://openalex.org/W2156787910"],"abstract_inverted_index":{"Classification":[0],"techniques":[1],"for":[2],"hyperspectral":[3,89],"images":[4,60],"based":[5,49],"on":[6,50,86],"random":[7,32],"forest":[8],"(RF)":[9],"ensembles":[10],"and":[11,35,95,113],"extended":[12],"multiextinction":[13],"profiles":[14],"(EMEPs)":[15],"are":[16,39,48,56],"proposed":[17,82,107],"as":[18],"a":[19,74],"means":[20],"of":[21,76,80,93,105],"improving":[22],"performance.":[23],"To":[24],"this":[25],"end,":[26],"five":[27],"strategies":[28],"-":[29,38],"bagging,":[30],"boosting,":[31],"subspace,":[33],"rotation-based,":[34],"boosted":[36,114],"rotation-based":[37,112,115],"used":[40],"to":[41,58,73],"construct":[42],"the":[43,59,63,81,91,102,106,122],"RF":[44],"ensembles.":[45],"EPs,":[46],"which":[47],"an":[51],"extrema-oriented":[52],"connected":[53],"filtering":[54],"technique,":[55],"applied":[57],"associated":[61],"with":[62],"first":[64],"informative":[65],"components":[66],"extracted":[67],"by":[68],"independent":[69],"component":[70],"analysis,":[71],"leading":[72],"set":[75],"EMEPs.":[77],"The":[78],"effectiveness":[79],"method":[83],"is":[84,120,126],"investigated":[85],"two":[87],"benchmark":[88],"images:":[90],"University":[92],"Pavia":[94],"Indian":[96],"Pines.":[97],"Comparative":[98],"experimental":[99],"evaluations":[100],"reveal":[101],"superior":[103],"performance":[104],"methods,":[108],"especially":[109],"those":[110],"employing":[111],"approaches.":[116],"An":[117],"additional":[118],"advantage":[119],"that":[121],"CPU":[123],"processing":[124],"time":[125],"acceptable.":[127]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":30},{"year":2020,"cited_by_count":26},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":13}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2017-10-06T00:00:00"}