{"id":"https://openalex.org/W2041100636","doi":"https://doi.org/10.1109/tgrs.2014.2345739","title":"Multiple Feature Learning for Hyperspectral Image Classification","display_name":"Multiple Feature Learning for Hyperspectral Image Classification","publication_year":2014,"publication_date":"2014-09-17","ids":{"openalex":"https://openalex.org/W2041100636","doi":"https://doi.org/10.1109/tgrs.2014.2345739","mag":"2041100636"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2014.2345739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2014.2345739","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/A5100362041","display_name":"Jun Li","orcid":"https://orcid.org/0000-0003-1613-9448"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jun Li","raw_affiliation_strings":["Sch. of Geogr. & Planning & Guangdong Key Lab. for Urbanization & Geo-Simulation, Sun Yat-sen Univ., Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sch. of Geogr. & Planning & Guangdong Key Lab. for Urbanization & Geo-Simulation, Sun Yat-sen Univ., Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031729932","display_name":"Xin Huang","orcid":"https://orcid.org/0000-0002-5625-0338"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Huang","raw_affiliation_strings":["[State Key Lab. of Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China]"],"affiliations":[{"raw_affiliation_string":"[State Key Lab. of Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China]","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006623289","display_name":"Paolo Gamba","orcid":"https://orcid.org/0000-0002-9576-6337"},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Gamba","raw_affiliation_strings":["[Telecommun. & Remote Sensing Lab., Univ. of Pavia, Pavia, Italy]"],"affiliations":[{"raw_affiliation_string":"[Telecommun. & Remote Sensing Lab., Univ. of Pavia, Pavia, Italy]","institution_ids":["https://openalex.org/I25217355"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017508063","display_name":"Jos\u00e9 M. Bioucas\u2010Dias","orcid":"https://orcid.org/0000-0002-0166-5149"},"institutions":[{"id":"https://openalex.org/I4210120471","display_name":"Instituto de Telecomunica\u00e7\u00f5es","ror":"https://ror.org/02ht4fk33","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210120471"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jose M. Bioucas Bioucas-Dias","raw_affiliation_strings":["Inst. de Telecomun., Univ. de Lisboa, Lisbon, Portugal"],"affiliations":[{"raw_affiliation_string":"Inst. de Telecomun., Univ. de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I4210120471"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100673818","display_name":"Liangpei Zhang","orcid":"https://orcid.org/0000-0001-6890-3650"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangpei Zhang","raw_affiliation_strings":["[State Key Lab. of Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China]"],"affiliations":[{"raw_affiliation_string":"[State Key Lab. of Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China]","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035508615","display_name":"J\u00f3n Atli Benediktsson","orcid":"https://orcid.org/0000-0003-0621-9647"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Jon Atli Benediktsson","raw_affiliation_strings":["[Fac. of Electr. & Comput. Eng., Univ. of Iceland, Reykjavik, Iceland]"],"affiliations":[{"raw_affiliation_string":"[Fac. of Electr. & Comput. Eng., Univ. of Iceland, Reykjavik, Iceland]","institution_ids":["https://openalex.org/I165368041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054292278","display_name":"Antonio Plaza","orcid":"https://orcid.org/0000-0002-9613-1659"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Plaza","raw_affiliation_strings":["Dept. of Technol. of Comput. & Commun., Univ. of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Dept. of Technol. of Comput. & Commun., Univ. of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100362041"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":53.1084,"has_fulltext":false,"cited_by_count":314,"citation_normalized_percentile":{"value":0.99916187,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"53","issue":"3","first_page":"1592","last_page":"1606"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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":0.9930999875068665,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9605000019073486,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8391474485397339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.669661283493042},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5892783403396606},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.5792521238327026},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5754724740982056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5647594332695007},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5477981567382812},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4844215214252472},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4834766983985901},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4560719132423401},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.4509066641330719},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.449695885181427},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42381593585014343},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3665168881416321},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35065892338752747},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2451665699481964},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21154865622520447}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8391474485397339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.669661283493042},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5892783403396606},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.5792521238327026},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5754724740982056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5647594332695007},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5477981567382812},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4844215214252472},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4834766983985901},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4560719132423401},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.4509066641330719},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.449695885181427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42381593585014343},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3665168881416321},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35065892338752747},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2451665699481964},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21154865622520447},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2014.2345739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2014.2345739","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:CiteSeerX.psu:10.1.1.704.3568","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.704.3568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.umbc.edu/rssipl/people/aplaza/Papers/Journals/2015.TGRS.Multiple.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1522547150","https://openalex.org/W1974398971","https://openalex.org/W1977461281","https://openalex.org/W1985973695","https://openalex.org/W1998030734","https://openalex.org/W2001298023","https://openalex.org/W2043665634","https://openalex.org/W2069231830","https://openalex.org/W2078495963","https://openalex.org/W2083541351","https://openalex.org/W2086762254","https://openalex.org/W2087263574","https://openalex.org/W2101365302","https://openalex.org/W2104269704","https://openalex.org/W2108917905","https://openalex.org/W2113464037","https://openalex.org/W2114819256","https://openalex.org/W2115451191","https://openalex.org/W2117633874","https://openalex.org/W2124547294","https://openalex.org/W2127199143","https://openalex.org/W2131697388","https://openalex.org/W2134594501","https://openalex.org/W2136251662","https://openalex.org/W2136625467","https://openalex.org/W2146611644","https://openalex.org/W2150579376","https://openalex.org/W2156787910","https://openalex.org/W2162480849","https://openalex.org/W2162698522","https://openalex.org/W2164330327","https://openalex.org/W2168481151","https://openalex.org/W3144619878","https://openalex.org/W4320339642"],"related_works":["https://openalex.org/W2132083814","https://openalex.org/W2725311638","https://openalex.org/W2123146423","https://openalex.org/W2091950550","https://openalex.org/W2570832236","https://openalex.org/W2599254681","https://openalex.org/W2144299089","https://openalex.org/W2133046540","https://openalex.org/W3092342941","https://openalex.org/W4388570703"],"abstract_inverted_index":{"Abstract\u2014Hyperspectral":[0],"image":[1],"classification":[2,31],"has":[3,109],"been":[4,22,110],"an":[5],"active":[6],"topic":[7],"of":[8,19,86,120],"research":[9],"in":[10,53,100,132],"recent":[11],"years.":[12],"In":[13],"the":[14,34,41,63,83,87,96,101],"past,":[15],"many":[16],"different":[17],"types":[18],"features":[20,47,70],"have":[21,39,56,68],"extracted":[23],"(using":[24],"both":[25],"linear":[26],"and":[27],"nonlinear":[28,73],"strategies)":[29],"for":[30],"problems.":[32],"On":[33,62],"one":[35],"hand,":[36,65],"some":[37],"approaches":[38],"exploited":[40,69],"original":[42,88],"spectral":[43],"information":[44,52,98],"or":[45,92,127],"other":[46,64,66],"linearly":[48,60],"derived":[49],"from":[50],"such":[51,122],"order":[54,133],"to":[55,76,80,93,112,115,134],"classes":[57],"which":[58],"are":[59],"separable.":[61],"techniques":[67,113],"obtained":[71],"through":[72],"transformations":[74],"intended":[75],"reduce":[77],"data":[78,89],"dimensionality,":[79],"better":[81],"model":[82],"inherent":[84],"nonlinearity":[85],"(e.g.,":[90,103],"kernels)":[91],"adequately":[94],"exploit":[95,116],"spatial":[97],"contained":[99],"scene":[102],"using":[104],"morphological":[105],"analysis).":[106],"Special":[107],"attention":[108],"given":[111],"able":[114],"a":[117],"single":[118],"kind":[119],"features,":[121],"as":[123],"composite":[124],"kernel":[125,129],"learning":[126],"multiple":[128,137],"learning,":[130],"developed":[131],"deal":[135],"with":[136],"kernels.":[138],"However,":[139],"few":[140]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":33},{"year":2019,"cited_by_count":45},{"year":2018,"cited_by_count":44},{"year":2017,"cited_by_count":57},{"year":2016,"cited_by_count":45},{"year":2015,"cited_by_count":14}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}
