{"id":"https://openalex.org/W3013868170","doi":"https://doi.org/10.1109/tnnls.2020.2978760","title":"Naive Gabor Networks for Hyperspectral Image Classification","display_name":"Naive Gabor Networks for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-03-24","ids":{"openalex":"https://openalex.org/W3013868170","doi":"https://doi.org/10.1109/tnnls.2020.2978760","mag":"3013868170","pmid":"https://pubmed.ncbi.nlm.nih.gov/32217488"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2020.2978760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.2978760","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5103109240","display_name":"Chenying Liu","orcid":"https://orcid.org/0000-0001-9172-3586"},"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":"Chenying Liu","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","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":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040061834","display_name":"Lin He","orcid":"https://orcid.org/0000-0003-3801-7257"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin He","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","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":["Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"affiliations":[{"raw_affiliation_string":"Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067097659","display_name":"Shutao Li","orcid":"https://orcid.org/0000-0002-0585-9848"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutao Li","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100758169","display_name":"Bo Li","orcid":"https://orcid.org/0000-0001-5980-4861"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Li","raw_affiliation_strings":["Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing, China","State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5103109240"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":8.3007,"has_fulltext":false,"cited_by_count":64,"citation_normalized_percentile":{"value":0.97660978,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"32","issue":"1","first_page":"376","last_page":"390"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9940999746322632,"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":0.9919999837875366,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gabor-wavelet","display_name":"Gabor wavelet","score":0.7398595213890076},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7311693429946899},{"id":"https://openalex.org/keywords/gabor-filter","display_name":"Gabor filter","score":0.7001957893371582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6890161037445068},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6059877872467041},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5639263391494751},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5286365747451782},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.521575391292572},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.4724823832511902},{"id":"https://openalex.org/keywords/gabor-transform","display_name":"Gabor transform","score":0.45256805419921875},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.35481634736061096},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3282494843006134},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3170366883277893},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2893381714820862},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.24170204997062683},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.17568856477737427}],"concepts":[{"id":"https://openalex.org/C136902061","wikidata":"https://www.wikidata.org/wiki/Q16981559","display_name":"Gabor wavelet","level":5,"score":0.7398595213890076},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7311693429946899},{"id":"https://openalex.org/C2779883129","wikidata":"https://www.wikidata.org/wiki/Q2447890","display_name":"Gabor filter","level":3,"score":0.7001957893371582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6890161037445068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6059877872467041},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5639263391494751},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5286365747451782},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.521575391292572},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.4724823832511902},{"id":"https://openalex.org/C173149727","wikidata":"https://www.wikidata.org/wiki/Q996397","display_name":"Gabor transform","level":4,"score":0.45256805419921875},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35481634736061096},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3282494843006134},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3170366883277893},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2893381714820862},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.24170204997062683},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.17568856477737427},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.0},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.0},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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":2,"locations":[{"id":"doi:10.1109/tnnls.2020.2978760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.2978760","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:32217488","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32217488","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2294148482","display_name":null,"funder_award_id":"61901208","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2336062148","display_name":null,"funder_award_id":"2016A030313516","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G4142269679","display_name":null,"funder_award_id":"61571195","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4690249876","display_name":null,"funder_award_id":"2017A030313382","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6004836032","display_name":null,"funder_award_id":"20192BAB217003","funder_id":"https://openalex.org/F4320322665","funder_display_name":"Natural Science Foundation of Jiangxi Province"},{"id":"https://openalex.org/G6321125736","display_name":null,"funder_award_id":"2016A030313254","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G8240734429","display_name":null,"funder_award_id":"61771496","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/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320322665","display_name":"Natural Science Foundation of Jiangxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W196871588","https://openalex.org/W1594551768","https://openalex.org/W1914401667","https://openalex.org/W1999334096","https://openalex.org/W2001298023","https://openalex.org/W2056983531","https://openalex.org/W2075529649","https://openalex.org/W2114819256","https://openalex.org/W2142232076","https://openalex.org/W2146769544","https://openalex.org/W2163346236","https://openalex.org/W2163605009","https://openalex.org/W2404926044","https://openalex.org/W2538566640","https://openalex.org/W2547018007","https://openalex.org/W2548791488","https://openalex.org/W2558098092","https://openalex.org/W2576915720","https://openalex.org/W2593709294","https://openalex.org/W2598997103","https://openalex.org/W2610691757","https://openalex.org/W2614256707","https://openalex.org/W2614286896","https://openalex.org/W2621462870","https://openalex.org/W2767651786","https://openalex.org/W2767805377","https://openalex.org/W2768537477","https://openalex.org/W2772452219","https://openalex.org/W2781659088","https://openalex.org/W2803149118","https://openalex.org/W2803164693","https://openalex.org/W2805671481","https://openalex.org/W2807793257","https://openalex.org/W2830936856","https://openalex.org/W2883305476","https://openalex.org/W2888119354","https://openalex.org/W2889835556","https://openalex.org/W2900375708","https://openalex.org/W2942454403","https://openalex.org/W2963325933","https://openalex.org/W2963623651","https://openalex.org/W2963744427","https://openalex.org/W2973818247","https://openalex.org/W3035558131","https://openalex.org/W3099211682","https://openalex.org/W3100011500","https://openalex.org/W3101446407","https://openalex.org/W3103753223","https://openalex.org/W4300686774","https://openalex.org/W6682747227","https://openalex.org/W6684191040","https://openalex.org/W6725287276","https://openalex.org/W6734728544"],"related_works":["https://openalex.org/W2070838085","https://openalex.org/W2495360253","https://openalex.org/W3156532881","https://openalex.org/W2382852560","https://openalex.org/W2355879620","https://openalex.org/W1830749786","https://openalex.org/W2066448268","https://openalex.org/W2162496653","https://openalex.org/W2373012758","https://openalex.org/W2103325943"],"abstract_inverted_index":{"Recently,":[0],"many":[1,64],"convolutional":[2],"neural":[3],"network":[4],"(CNN)":[5],"methods":[6],"have":[7],"been":[8],"designed":[9,136],"for":[10,86],"hyperspectral":[11],"image":[12],"(HSI)":[13],"classification":[14],"since":[15],"CNNs":[16],"are":[17],"able":[18],"to":[19,51,106,137,171,174],"produce":[20],"good":[21],"representations":[22],"of":[23,32,46,102,110,123,147,153,179,234],"data,":[24],"which":[25,133],"greatly":[26],"benefits":[27],"from":[28],"a":[29,37,43,58,144,201,210,238],"huge":[30],"number":[31,45,109],"parameters.":[33],"However,":[34],"solving":[35],"such":[36],"high-dimensional":[38],"optimization":[39],"problem":[40,61],"often":[41],"requires":[42],"large":[44],"training":[47,240],"samples":[48],"in":[49,74,90,99,200,209],"order":[50],"avoid":[52],"overfitting.":[53],"In":[54],"addition,":[55],"it":[56],"is":[57,134],"typical":[59],"nonconvex":[60],"affected":[62],"by":[63,156],"local":[65,148,176],"minima":[66],"and":[67,94,113,150],"flat":[68],"regions.":[69],"To":[70],"address":[71],"these":[72],"problems,":[73],"this":[75,191],"article,":[76],"we":[77,126],"introduce":[78],"the":[79,87,91,100,108,115,121,139,157,161,165,169,175,180,195,232],"naive":[80],"Gabor":[81,103,131,140,163,198],"networks":[82],"or":[83],"Gabor-Nets":[84,167,206,219,228],"that,":[85],"first":[88],"time":[89],"literature,":[92],"design":[93],"learn":[95],"CNN":[96,212],"kernels":[97],"strictly":[98],"form":[101],"filters,":[104],"aiming":[105],"reduce":[107],"involved":[111],"parameters":[112],"constrain":[114],"solution":[116],"space":[117],"and,":[118,183],"hence,":[119],"improve":[120,231],"performances":[122],"CNNs.":[124],"Specifically,":[125],"develop":[127],"an":[128],"innovative":[129],"phase-induced":[130,162],"kernel,":[132,164],"trickily":[135],"perform":[138,208],"feature":[141],"learning":[142],"via":[143],"linear":[145],"combination":[146],"low-frequency":[149],"high-frequency":[151],"components":[152],"data":[154,182],"controlled":[155],"kernel":[158,192],"phase.":[159],"With":[160],"proposed":[166,227],"gains":[168],"ability":[170],"automatically":[172],"adapt":[173],"harmonic":[177,188],"characteristics":[178],"HSI":[181],"thus,":[184],"yields":[185],"more":[186],"representative":[187],"features.":[189],"Also,":[190],"can":[193,229],"fulfill":[194],"traditional":[196],"complex-valued":[197],"filtering":[199],"real-valued":[202],"manner,":[203],"hence":[204],"making":[205],"easily":[207],"usual":[211],"thread.":[213],"We":[214],"evaluated":[215],"our":[216,226],"newly":[217],"developed":[218],"on":[220],"three":[221],"well-known":[222],"HSIs,":[223],"suggesting":[224],"that":[225],"significantly":[230],"performance":[233],"CNNs,":[235],"particularly":[236],"with":[237],"small":[239],"set.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}