{"id":"https://openalex.org/W2889861425","doi":"https://doi.org/10.1109/tgrs.2018.2865953","title":"Hyperspectral Image Classification With Squeeze Multibias Network","display_name":"Hyperspectral Image Classification With Squeeze Multibias Network","publication_year":2018,"publication_date":"2018-09-13","ids":{"openalex":"https://openalex.org/W2889861425","doi":"https://doi.org/10.1109/tgrs.2018.2865953","mag":"2889861425"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2018.2865953","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2865953","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/A5065061505","display_name":"Leyuan Fang","orcid":"https://orcid.org/0000-0003-2351-4461"},"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":"Leyuan Fang","raw_affiliation_strings":["Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-2351-4461","affiliations":[{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102311190","display_name":"Guangyun Liu","orcid":null},"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":"Guangyun Liu","raw_affiliation_strings":["Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"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":["Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0585-9848","affiliations":[{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"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/I2801798921","display_name":"Helmholtz-Zentrum Dresden-Rossendorf","ror":"https://ror.org/01zy2cs03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921"]},{"id":"https://openalex.org/I4210148560","display_name":"Helmholtz Institute Freiberg for Resource Technology","ror":"https://ror.org/04kdb0j04","country_code":"DE","type":"government","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Pedram Ghamisi","raw_affiliation_strings":["Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany"],"raw_orcid":"https://orcid.org/0000-0003-1203-741X","affiliations":[{"raw_affiliation_string":"Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany","institution_ids":["https://openalex.org/I2801798921","https://openalex.org/I4210148560"]}]},{"author_position":"last","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":["Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavk, Iceland"],"raw_orcid":"https://orcid.org/0000-0003-0621-9647","affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavk, Iceland","institution_ids":["https://openalex.org/I165368041"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":9.867,"has_fulltext":false,"cited_by_count":116,"citation_normalized_percentile":{"value":0.982496,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"57","issue":"3","first_page":"1291","last_page":"1301"},"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":0.9934999942779541,"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":0.98580002784729,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8010053634643555},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7802214622497559},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7500215768814087},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7351878881454468},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6832262873649597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6207066774368286},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5510179400444031},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47431111335754395},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4707173705101013},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43652260303497314},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4349030554294586},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2758381962776184}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8010053634643555},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7802214622497559},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7500215768814087},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7351878881454468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6832262873649597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6207066774368286},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5510179400444031},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47431111335754395},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4707173705101013},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43652260303497314},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4349030554294586},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2758381962776184},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2018.2865953","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2865953","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3693646142","display_name":"\u57fa\u4e8eOCT\u56fe\u50cf\u591a\u75c5\u53d8\u5206\u6790\u7684\u89c6\u7f51\u819c\u75be\u75c5\u81ea\u52a8\u8bca\u65ad\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61771192","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G898426514","display_name":null,"funder_award_id":"61520106001","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1491705651","https://openalex.org/W1521436688","https://openalex.org/W1593727536","https://openalex.org/W1665214252","https://openalex.org/W1939429412","https://openalex.org/W1978508564","https://openalex.org/W1990895816","https://openalex.org/W2004104348","https://openalex.org/W2016860790","https://openalex.org/W2029316659","https://openalex.org/W2041100636","https://openalex.org/W2041490442","https://openalex.org/W2046084233","https://openalex.org/W2046887992","https://openalex.org/W2051968191","https://openalex.org/W2052160904","https://openalex.org/W2059217921","https://openalex.org/W2072072671","https://openalex.org/W2078495963","https://openalex.org/W2085529604","https://openalex.org/W2090424610","https://openalex.org/W2097117768","https://openalex.org/W2097915756","https://openalex.org/W2109255472","https://openalex.org/W2112796928","https://openalex.org/W2114819256","https://openalex.org/W2130942839","https://openalex.org/W2135758523","https://openalex.org/W2136251662","https://openalex.org/W2136922672","https://openalex.org/W2163605009","https://openalex.org/W2166923144","https://openalex.org/W2167998037","https://openalex.org/W2314785379","https://openalex.org/W2315347323","https://openalex.org/W2339741109","https://openalex.org/W2345128667","https://openalex.org/W2500751094","https://openalex.org/W2548791488","https://openalex.org/W2577238056","https://openalex.org/W2582369608","https://openalex.org/W2595902385","https://openalex.org/W2620547787","https://openalex.org/W2620858446","https://openalex.org/W2743255627","https://openalex.org/W2750085043","https://openalex.org/W2759518055","https://openalex.org/W2765739551","https://openalex.org/W2768211636","https://openalex.org/W2772147448","https://openalex.org/W2779054585","https://openalex.org/W2789516031","https://openalex.org/W2792332881","https://openalex.org/W2793645503","https://openalex.org/W2795547044","https://openalex.org/W2804902458","https://openalex.org/W2962911728","https://openalex.org/W2963609427","https://openalex.org/W3100245404","https://openalex.org/W6637242042","https://openalex.org/W6679436768","https://openalex.org/W6684191040","https://openalex.org/W6703703660"],"related_works":["https://openalex.org/W2964954556","https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661"],"abstract_inverted_index":{"A":[0],"convolutional":[1,61,152],"neural":[2],"network":[3,92],"(CNN)":[4],"has":[5],"recently":[6],"demonstrated":[7],"its":[8],"outstanding":[9],"capability":[10],"for":[11,96,143],"the":[12,28,52,56,65,85,100,105,113,122,140,146,150,163,168,172,188,191],"classification":[13,53,179,198],"of":[14,46,55,71,125,165,190],"hyperspectral":[15],"images":[16],"(HSIs).":[17],"Typical":[18],"CNN-based":[19],"methods":[20],"usually":[21],"adopt":[22],"image":[23,33],"patches":[24,127],"as":[25],"inputs":[26],"to":[27,74,133],"network.":[29],"However,":[30],"a":[31,68,88,155],"fixed-size":[32],"patch":[34],"in":[35,64,167],"HSI":[36,97],"with":[37,154],"complex":[38],"spatial":[39],"contexts":[40],"may":[41],"contain":[42],"multiple":[43,129],"ground":[44,135],"objects":[45],"different":[47,134],"classes,":[48],"which":[49,77,109,159],"will":[50,78],"deteriorate":[51],"performance":[54],"CNN.":[57],"In":[58],"addition,":[59],"traditional":[60,151],"layers":[62],"adopted":[63],"CNN":[66],"have":[67],"huge":[69],"amount":[70],"parameters":[72,166],"needed":[73],"be":[75],"tuned,":[76],"cause":[79],"high":[80,178],"computational":[81],"cost.":[82],"To":[83],"address":[84],"above-mentioned":[86],"issues,":[87],"novel":[89],"squeeze":[90,156],"multibias":[91,106,111],"(SMBN)":[93],"is":[94],"proposed":[95,101,147,192],"classification.":[98,144],"Specifically,":[99],"SMBN":[102,148,193],"first":[103],"introduces":[104],"module":[107],"(MBM),":[108],"incorporates":[110],"into":[112,128],"rectified":[114],"linear":[115],"unit":[116],"layers.":[117],"The":[118],"MBM":[119],"can":[120,160],"decouple":[121],"feature":[123],"maps":[124,131,142],"input":[126],"response":[130],"(corresponding":[132],"objects)":[136],"and":[137],"adaptively":[138],"select":[139],"meaningful":[141],"Furthermore,":[145],"replaces":[149],"layer":[153],"convolution":[157],"module,":[158],"greatly":[161],"reduce":[162],"number":[164],"network,":[169],"thus":[170],"saving":[171],"running":[173],"time,":[174],"while":[175],"still":[176],"maintaining":[177],"accuracy.":[180],"Experimental":[181],"results":[182],"on":[183],"three":[184],"real":[185],"HSIs":[186],"demonstrate":[187],"superiority":[189],"method":[194],"over":[195],"several":[196],"state-of-the-art":[197],"approaches.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":23},{"year":2018,"cited_by_count":1}],"updated_date":"2026-08-29T07:29:34.045763","created_date":"2025-10-10T00:00:00"}