{"id":"https://openalex.org/W4213388517","doi":"https://doi.org/10.3390/rs14041038","title":"Meta-Learner Hybrid Models to Classify Hyperspectral Images","display_name":"Meta-Learner Hybrid Models to Classify Hyperspectral Images","publication_year":2022,"publication_date":"2022-02-21","ids":{"openalex":"https://openalex.org/W4213388517","doi":"https://doi.org/10.3390/rs14041038"},"language":"en","primary_location":{"id":"doi:10.3390/rs14041038","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14041038","pdf_url":"https://www.mdpi.com/2072-4292/14/4/1038/pdf?version=1645524590","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/4/1038/pdf?version=1645524590","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068367341","display_name":"Dalal AL-Alimi","orcid":"https://orcid.org/0000-0002-0322-3694"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dalal AL-Alimi","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan 430074, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067624332","display_name":"Mohammed A. A. Al\u2010qaness","orcid":"https://orcid.org/0000-0002-6956-7641"},"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"]},{"id":"https://openalex.org/I170535673","display_name":"Sana'a University","ror":"https://ror.org/04hcvaf32","country_code":"YE","type":"education","lineage":["https://openalex.org/I170535673"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN","YE"],"is_corresponding":true,"raw_author_name":"Mohammed A. A. Al-qaness","raw_affiliation_strings":["Faculty of Engineering, Sana\u2019a University, Sana\u2019a 12544, Yemen","State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China","Faculty of Engineering, Sana'a University, Sana'a 12544, Yemen"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Sana\u2019a University, Sana\u2019a 12544, Yemen","institution_ids":["https://openalex.org/I170535673"]},{"raw_affiliation_string":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]},{"raw_affiliation_string":"Faculty of Engineering, Sana'a University, Sana'a 12544, Yemen","institution_ids":["https://openalex.org/I170535673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038861185","display_name":"Zhihua Cai","orcid":"https://orcid.org/0000-0003-0020-6503"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihua Cai","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan 430074, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011155311","display_name":"Abdelghani Dahou","orcid":"https://orcid.org/0000-0003-4561-2185"},"institutions":[{"id":"https://openalex.org/I22223346","display_name":"Ahmed Draia University","ror":"https://ror.org/01k476402","country_code":"DZ","type":"education","lineage":["https://openalex.org/I22223346"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Abdelghani Dahou","raw_affiliation_strings":["Department of Mathematics and Computer Science, Faculty of Science and Technology, University of Ahmed DRAIA, Adrar 01000, Algeria"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Faculty of Science and Technology, University of Ahmed DRAIA, Adrar 01000, Algeria","institution_ids":["https://openalex.org/I22223346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101871969","display_name":"Yuxiang Shao","orcid":"https://orcid.org/0009-0002-5493-5517"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxiang Shao","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan 430074, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007092484","display_name":"Sakinatu Issaka","orcid":"https://orcid.org/0000-0002-4200-2499"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sakinatu Issaka","raw_affiliation_strings":["School of Environmental Studies, China University of Geosciences, Wuhan 430074, China"],"affiliations":[{"raw_affiliation_string":"School of Environmental Studies, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5067624332"],"corresponding_institution_ids":["https://openalex.org/I170535673","https://openalex.org/I37461747","https://openalex.org/I4210118728"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.7512,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.91165756,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"14","issue":"4","first_page":"1038","last_page":"1038"},"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":0.9977999925613403,"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":0.9768000245094299,"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/computer-science","display_name":"Computer science","score":0.8047187328338623},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7584816217422485},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6894217729568481},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6304396390914917},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5910360217094421},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5862168073654175},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5029312968254089},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.45753246545791626},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4396907389163971},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.430072546005249},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.41064849495887756},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37058722972869873},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.33442428708076477},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.2327599823474884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08764892816543579}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8047187328338623},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7584816217422485},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6894217729568481},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6304396390914917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5910360217094421},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5862168073654175},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5029312968254089},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.45753246545791626},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4396907389163971},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.430072546005249},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.41064849495887756},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37058722972869873},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.33442428708076477},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2327599823474884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08764892816543579},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14041038","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14041038","pdf_url":"https://www.mdpi.com/2072-4292/14/4/1038/pdf?version=1645524590","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3d89f6bb54be4a468e68707d1bdc9203","is_oa":true,"landing_page_url":"https://doaj.org/article/3d89f6bb54be4a468e68707d1bdc9203","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 4, p 1038 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/4/1038/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14041038","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 14; Issue 4; Pages: 1038","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14041038","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14041038","pdf_url":"https://www.mdpi.com/2072-4292/14/4/1038/pdf?version=1645524590","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.41999998688697815}],"awards":[],"funders":[{"id":"https://openalex.org/F4320326938","display_name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing","ror":"https://ror.org/02bpap860"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4213388517.pdf","grobid_xml":"https://content.openalex.org/works/W4213388517.grobid-xml"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W1967782666","https://openalex.org/W2003543118","https://openalex.org/W2008509935","https://openalex.org/W2008847349","https://openalex.org/W2008997808","https://openalex.org/W2020537481","https://openalex.org/W2038705219","https://openalex.org/W2097915756","https://openalex.org/W2104269704","https://openalex.org/W2221243399","https://openalex.org/W2336021816","https://openalex.org/W2565639579","https://openalex.org/W2626046541","https://openalex.org/W2732412926","https://openalex.org/W2752782242","https://openalex.org/W2794242089","https://openalex.org/W2801400875","https://openalex.org/W2804458818","https://openalex.org/W2809563660","https://openalex.org/W2889326414","https://openalex.org/W2890267291","https://openalex.org/W2894763306","https://openalex.org/W2898532184","https://openalex.org/W2908009020","https://openalex.org/W2914331134","https://openalex.org/W2915459603","https://openalex.org/W2921243146","https://openalex.org/W2942170965","https://openalex.org/W2942454403","https://openalex.org/W2966187434","https://openalex.org/W2971690561","https://openalex.org/W2975372759","https://openalex.org/W2979950223","https://openalex.org/W2980998357","https://openalex.org/W2987305265","https://openalex.org/W2991616716","https://openalex.org/W3002674187","https://openalex.org/W3002842489","https://openalex.org/W3004925702","https://openalex.org/W3008119735","https://openalex.org/W3011495011","https://openalex.org/W3014628500","https://openalex.org/W3017845037","https://openalex.org/W3023351371","https://openalex.org/W3034054712","https://openalex.org/W3036828293","https://openalex.org/W3043181422","https://openalex.org/W3045811518","https://openalex.org/W3047074348","https://openalex.org/W3085067733","https://openalex.org/W3086038210","https://openalex.org/W3089160504","https://openalex.org/W3092534080","https://openalex.org/W3120426666","https://openalex.org/W3120948300","https://openalex.org/W3131860561","https://openalex.org/W3169426236","https://openalex.org/W3172902538","https://openalex.org/W3194272457","https://openalex.org/W3198631380","https://openalex.org/W4200354142","https://openalex.org/W4243367342","https://openalex.org/W4299316249","https://openalex.org/W6642198582"],"related_works":["https://openalex.org/W2379488555","https://openalex.org/W2753886092","https://openalex.org/W2152632846","https://openalex.org/W1992961908","https://openalex.org/W2014683590","https://openalex.org/W2132083814","https://openalex.org/W2944973397","https://openalex.org/W3138125914","https://openalex.org/W2359742711","https://openalex.org/W2139392257"],"abstract_inverted_index":{"Hyperspectral":[0],"(HS)":[1],"images":[2,6,79],"are":[3,8,23],"adjacent":[4],"band":[5],"that":[7,22,40,157],"generally":[9],"used":[10],"in":[11,29],"remote-sensing":[12],"applications.":[13],"They":[14],"have":[15],"numerous":[16],"spatial":[17],"and":[18,56,67,89,94,98,118,143,169,171,177],"spectral":[19],"information":[20],"bands":[21],"extremely":[24],"useful":[25],"for":[26,166],"material":[27],"detection":[28],"various":[30],"fields.":[31],"However,":[32],"their":[33,42],"high":[34],"dimensionality":[35],"is":[36],"a":[37,76],"big":[38],"challenge":[39],"affects":[41],"overall":[43],"performance.":[44,182],"A":[45],"new":[46,123],"data":[47,57],"normalization":[48,138],"method":[49],"was":[50],"developed":[51],"to":[52,86,110],"enhance":[53],"the":[54,60,83,96,112,115,122,141,153,158,161,180],"variations":[55],"distribution":[58],"using":[59,82,147],"output":[61,113],"of":[62,101,114],"principal":[63],"component":[64],"analysis":[65],"(PCA)":[66],"quantile":[68],"transformation,":[69],"called":[70,126],"QPCA.":[71],"This":[72],"paper":[73],"also":[74],"proposes":[75],"novel":[77],"HS":[78],"classification":[80],"framework":[81,134,162],"meta-learner":[84,127],"technique":[85],"train":[87,119],"multi-class":[88],"multi-size":[90,99],"datasets":[91,170],"by":[92,164,173],"concatenating":[93],"training":[95],"hybrid":[97,128],"kernel":[100],"convolutional":[102],"neural":[103],"networks":[104],"(CNN).":[105],"The":[106,131],"high-level":[107],"model":[108],"works":[109],"combine":[111],"lower-level":[116],"models":[117,129,168],"them":[120],"with":[121,135],"input":[124],"data,":[125],"(MLHM).":[130],"proposed":[132],"MLHM":[133,178],"our":[136],"external":[137],"(QPCA)":[139],"improves":[140],"accuracy":[142,163],"outperforms":[144],"other":[145],"approaches":[146],"three":[148],"well-known":[149],"benchmark":[150],"datasets.":[151],"Moreover,":[152],"evaluation":[154],"outcomes":[155],"showed":[156],"QPCA":[159],"enhanced":[160],"13%":[165],"most":[167],"others":[172],"more":[174],"than":[175],"25%,":[176],"provided":[179],"best":[181]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}