{"id":"https://openalex.org/W4361009738","doi":"https://doi.org/10.3390/rs15071758","title":"Multi-Scale Spectral-Spatial Attention Network for Hyperspectral Image Classification Combining 2D Octave and 3D Convolutional Neural Networks","display_name":"Multi-Scale Spectral-Spatial Attention Network for Hyperspectral Image Classification Combining 2D Octave and 3D Convolutional Neural Networks","publication_year":2023,"publication_date":"2023-03-24","ids":{"openalex":"https://openalex.org/W4361009738","doi":"https://doi.org/10.3390/rs15071758"},"language":"en","primary_location":{"id":"doi:10.3390/rs15071758","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15071758","pdf_url":"https://www.mdpi.com/2072-4292/15/7/1758/pdf?version=1679840902","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/2072-4292/15/7/1758/pdf?version=1679840902","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036534306","display_name":"Lianhui Liang","orcid":"https://orcid.org/0000-0001-6958-0443"},"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":"Lianhui Liang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha 418002, China"],"raw_orcid":"https://orcid.org/0000-0001-6958-0443","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha 418002, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002395584","display_name":"Shaoquan Zhang","orcid":"https://orcid.org/0000-0002-1454-9665"},"institutions":[{"id":"https://openalex.org/I141103825","display_name":"Nanchang Institute of Technology","ror":"https://ror.org/00avfj807","country_code":"CN","type":"education","lineage":["https://openalex.org/I141103825"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaoquan Zhang","raw_affiliation_strings":["Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China"],"raw_orcid":"https://orcid.org/0000-0002-1454-9665","affiliations":[{"raw_affiliation_string":"Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China","institution_ids":["https://openalex.org/I141103825"]}]},{"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/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":"Jun Li","raw_affiliation_strings":["Hubei Key Laboratory of Intelligent Geo-Information Processing, School of Computer Science, China University of Geosciences, Wuhan 430078, China"],"raw_orcid":"https://orcid.org/0000-0003-1613-9448","affiliations":[{"raw_affiliation_string":"Hubei Key Laboratory of Intelligent Geo-Information Processing, School of Computer Science, China University of Geosciences, Wuhan 430078, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"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, Department of Technology of Computers and Communications, University of Extremadura, E-10071 Caceres, Spain"],"raw_orcid":"https://orcid.org/0000-0002-9613-1659","affiliations":[{"raw_affiliation_string":"Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, University of Extremadura, E-10071 Caceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086998101","display_name":"Zhi Cui","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":"Zhi Cui","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha 418002, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha 418002, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5002395584"],"corresponding_institution_ids":["https://openalex.org/I141103825"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.2825,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.89332966,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"15","issue":"7","first_page":"1758","last_page":"1758"},"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":0.9915000200271606,"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":0.9646999835968018,"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":0.7634624242782593},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7291200757026672},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6995218992233276},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6770197749137878},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6397439241409302},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6248986124992371},{"id":"https://openalex.org/keywords/octave","display_name":"Octave (electronics)","score":0.5537355542182922},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5407434105873108},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5314344763755798},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5073308348655701},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5053640007972717},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3543652296066284},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.20153087377548218},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15422877669334412}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7634624242782593},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7291200757026672},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6995218992233276},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6770197749137878},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6397439241409302},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6248986124992371},{"id":"https://openalex.org/C85841341","wikidata":"https://www.wikidata.org/wiki/Q1135984","display_name":"Octave (electronics)","level":2,"score":0.5537355542182922},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5407434105873108},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5314344763755798},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5073308348655701},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5053640007972717},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3543652296066284},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.20153087377548218},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15422877669334412},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":3,"locations":[{"id":"doi:10.3390/rs15071758","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15071758","pdf_url":"https://www.mdpi.com/2072-4292/15/7/1758/pdf?version=1679840902","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:46f9ec819cfa4b3f9c07ea3076257835","is_oa":true,"landing_page_url":"https://doaj.org/article/46f9ec819cfa4b3f9c07ea3076257835","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 7, p 1758 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/7/1758/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15071758","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 15; Issue 7; Pages: 1758","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15071758","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15071758","pdf_url":"https://www.mdpi.com/2072-4292/15/7/1758/pdf?version=1679840902","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":[{"id":"https://metadata.un.org/sdg/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G6716103886","display_name":null,"funder_award_id":"T2225019","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/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4361009738.pdf"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W248389711","https://openalex.org/W1939429412","https://openalex.org/W2029316659","https://openalex.org/W2035549557","https://openalex.org/W2090424610","https://openalex.org/W2113464037","https://openalex.org/W2136251662","https://openalex.org/W2144966944","https://openalex.org/W2152438175","https://openalex.org/W2158400785","https://openalex.org/W2159070926","https://openalex.org/W2302255633","https://openalex.org/W2346557146","https://openalex.org/W2500751094","https://openalex.org/W2562461367","https://openalex.org/W2582369608","https://openalex.org/W2614256707","https://openalex.org/W2767805377","https://openalex.org/W2822065499","https://openalex.org/W2914331134","https://openalex.org/W2938458886","https://openalex.org/W2942170965","https://openalex.org/W2942454403","https://openalex.org/W2948157022","https://openalex.org/W2962770389","https://openalex.org/W2963446712","https://openalex.org/W2971007343","https://openalex.org/W2975506318","https://openalex.org/W2992027343","https://openalex.org/W2997343747","https://openalex.org/W3004617095","https://openalex.org/W3014253313","https://openalex.org/W3034552520","https://openalex.org/W3043181422","https://openalex.org/W3043183554","https://openalex.org/W3093701503","https://openalex.org/W3098388691","https://openalex.org/W3103753223","https://openalex.org/W3137622667","https://openalex.org/W3165209762","https://openalex.org/W3199738078","https://openalex.org/W4206702230","https://openalex.org/W4240485910","https://openalex.org/W4281394103","https://openalex.org/W4285107185","https://openalex.org/W4285248393","https://openalex.org/W4294643233","https://openalex.org/W4312395821","https://openalex.org/W4312455041","https://openalex.org/W4313558738","https://openalex.org/W6677065643"],"related_works":["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/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W3129431614"],"abstract_inverted_index":{"Traditional":[0],"convolutional":[1,105],"neural":[2],"networks":[3,102,134],"(CNNs)":[4],"can":[5],"be":[6],"applied":[7,129,158],"to":[8,38,108,130,135,159],"obtain":[9,109],"the":[10,44,52,63,120,123,150,161],"spectral-spatial":[11,79],"feature":[12,25,113,138],"information":[13,42,114,148],"from":[14],"hyperspectral":[15],"images":[16],"(HSIs).":[17],"However,":[18,51],"they":[19],"often":[20],"introduce":[21,58],"significant":[22,137],"redundant":[23,41],"spatial":[24,40,111],"information.":[26],"The":[27],"octave":[28,54,85,96],"convolution":[29,97],"network":[30,45],"is":[31,157],"frequently":[32],"utilized":[33],"instead":[34],"of":[35,43],"traditional":[36],"CNN":[37],"decrease":[39],"and":[46,61,86,98,115,122,140,191],"extend":[47],"its":[48],"receptive":[49],"field.":[50],"3D":[53,87,99],"convolution-based":[55],"approaches":[56],"may":[57],"extensive":[59],"parameters":[60],"complicate":[62],"network.":[64],"To":[65],"solve":[66],"these":[67,131],"issues,":[68],"we":[69],"propose":[70],"a":[71,77,153],"new":[72],"HSI":[73,171,183],"classification":[74],"approach":[75,177],"with":[76,103],"multi-scale":[78],"network-based":[80],"framework":[81],"that":[82,145,174],"combines":[83],"2D":[84,95],"CNNs.":[88],"Our":[89],"method,":[90],"called":[91],"MOCNN,":[92],"first":[93],"utilizes":[94],"DenseNet":[100],"branch":[101,133],"various":[104],"kernel":[106],"sizes":[107],"complex":[110],"contextual":[112],"spectral":[116,124,143],"characteristics,":[117],"separately.":[118],"Moreover,":[119],"channel":[121],"attention":[125],"mechanisms":[126],"are,":[127],"respectively,":[128],"two":[132],"emphasize":[136],"regions":[139],"certain":[141],"important":[142],"bands":[144],"comprise":[146],"discriminative":[147],"for":[149,182],"categorization.":[151],"Furthermore,":[152],"sample":[154,162,193],"balancing":[155],"strategy":[156],"address":[160],"imbalance":[163],"problem.":[164],"Expansive":[165],"experiments":[166],"are":[167],"undertaken":[168],"on":[169],"four":[170],"datasets,":[172],"demonstrating":[173],"our":[175],"MOCNN":[176],"outperforms":[178],"several":[179],"other":[180],"methods":[181],"classification,":[184],"especially":[185],"in":[186],"scenarios":[187],"dominated":[188],"by":[189],"limited":[190],"imbalanced":[192],"data.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
