{"id":"https://openalex.org/W3094484482","doi":"https://doi.org/10.1109/tnnls.2020.3028945","title":"A<sup>3</sup> CLNN: Spatial, Spectral and Multiscale Attention ConvLSTM Neural Network for Multisource Remote Sensing Data Classification","display_name":"A<sup>3</sup> CLNN: Spatial, Spectral and Multiscale Attention ConvLSTM Neural Network for Multisource Remote Sensing Data Classification","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3094484482","doi":"https://doi.org/10.1109/tnnls.2020.3028945","mag":"3094484482","pmid":"https://pubmed.ncbi.nlm.nih.gov/33085622"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2020.3028945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3028945","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":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2204.04462","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015155189","display_name":"Heng-Chao Li","orcid":"https://orcid.org/0000-0002-9735-570X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Heng-Chao Li","raw_affiliation_strings":["Sichuan Provincial Key Laboratory of Information Coding and Transmission, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Sichuan Provincial Key Laboratory of Information Coding and Transmission, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067999166","display_name":"Wen-Shuai Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen-Shuai Hu","raw_affiliation_strings":["Sichuan Provincial Key Laboratory of Information Coding and Transmission, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Sichuan Provincial Key Laboratory of Information Coding and Transmission, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317994","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-7015-7335"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"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/A5033017179","display_name":"Qian Du","orcid":"https://orcid.org/0000-0001-8354-7500"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qian Du","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"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":["Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit&#x00E9;cnica, University of Extremadura, C&#x00E1;ceres, Spain","ceres, Spain","Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit&#x00E9","cnica, University of Extremadura, C&#x00E1"],"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit&#x00E9;cnica, University of Extremadura, C&#x00E1;ceres, Spain","institution_ids":["https://openalex.org/I80606768"]},{"raw_affiliation_string":"ceres, Spain","institution_ids":[]},{"raw_affiliation_string":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit&#x00E9","institution_ids":[]},{"raw_affiliation_string":"cnica, University of Extremadura, C&#x00E1","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5015155189"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":11.4695,"has_fulltext":false,"cited_by_count":137,"citation_normalized_percentile":{"value":0.98542017,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"33","issue":"2","first_page":"747","last_page":"761"},"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":0.9966999888420105,"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":0.9847000241279602,"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/computer-science","display_name":"Computer science","score":0.7389835119247437},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.716518759727478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5133220553398132},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5058695673942566},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4914196729660034},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.49121636152267456},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4861426055431366},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.45777201652526855},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45427072048187256},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.43399718403816223},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.43153390288352966},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.42989209294319153},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42048269510269165},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3504437506198883},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09710076451301575}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7389835119247437},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.716518759727478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5133220553398132},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5058695673942566},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4914196729660034},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.49121636152267456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4861426055431366},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.45777201652526855},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45427072048187256},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.43399718403816223},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.43153390288352966},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.42989209294319153},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42048269510269165},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3504437506198883},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09710076451301575},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2020.3028945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3028945","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:33085622","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33085622","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},{"id":"pmh:oai:arXiv.org:2204.04462","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.04462","pdf_url":"https://arxiv.org/pdf/2204.04462","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2204.04462","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.04462","pdf_url":"https://arxiv.org/pdf/2204.04462","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3552334747","display_name":null,"funder_award_id":"2682020XG02","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4677181399","display_name":null,"funder_award_id":"2682020ZT35","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7569220417","display_name":null,"funder_award_id":"61871335","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/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1497089125","https://openalex.org/W1521436688","https://openalex.org/W2008847349","https://openalex.org/W2011085793","https://openalex.org/W2012838735","https://openalex.org/W2022773386","https://openalex.org/W2029992428","https://openalex.org/W2038386419","https://openalex.org/W2064675550","https://openalex.org/W2067874135","https://openalex.org/W2087263574","https://openalex.org/W2097117768","https://openalex.org/W2122585011","https://openalex.org/W2133564696","https://openalex.org/W2152057649","https://openalex.org/W2152233525","https://openalex.org/W2314785379","https://openalex.org/W2320846209","https://openalex.org/W2346557146","https://openalex.org/W2500751094","https://openalex.org/W2548791488","https://openalex.org/W2550553598","https://openalex.org/W2600746131","https://openalex.org/W2602024454","https://openalex.org/W2606929568","https://openalex.org/W2609880332","https://openalex.org/W2738447277","https://openalex.org/W2752782242","https://openalex.org/W2765739551","https://openalex.org/W2768537477","https://openalex.org/W2770644742","https://openalex.org/W2781621993","https://openalex.org/W2792827505","https://openalex.org/W2811355488","https://openalex.org/W2888715336","https://openalex.org/W2890133123","https://openalex.org/W2890732922","https://openalex.org/W2898682679","https://openalex.org/W2900587135","https://openalex.org/W2901117552","https://openalex.org/W2913939882","https://openalex.org/W2914959431","https://openalex.org/W2936222941","https://openalex.org/W2937615289","https://openalex.org/W2950266692","https://openalex.org/W2951454267","https://openalex.org/W2961699889","https://openalex.org/W2963495494","https://openalex.org/W2969393175","https://openalex.org/W2999446243","https://openalex.org/W3004480865","https://openalex.org/W3101640299","https://openalex.org/W3102127038","https://openalex.org/W4225823706","https://openalex.org/W4240485910","https://openalex.org/W4299518610","https://openalex.org/W4309845474","https://openalex.org/W4320930577","https://openalex.org/W4385245566","https://openalex.org/W6628877408","https://openalex.org/W6638444622","https://openalex.org/W6679434410","https://openalex.org/W6682132143","https://openalex.org/W6739901393","https://openalex.org/W6746023985"],"related_works":["https://openalex.org/W2521519254","https://openalex.org/W3139833644","https://openalex.org/W3123110765","https://openalex.org/W4383553409","https://openalex.org/W2104948296","https://openalex.org/W1735800226","https://openalex.org/W4285172739","https://openalex.org/W3123208392","https://openalex.org/W2440023763","https://openalex.org/W2962474440"],"abstract_inverted_index":{"The":[0],"problem":[1],"of":[2,33,73,143],"effectively":[3],"exploiting":[4],"the":[5,31,110,131,141,172],"information":[6,105],"multiple":[7],"data":[8,35,91,136,168],"sources":[9],"has":[10],"become":[11],"a":[12,26,50,114,122,146,155],"relevant":[13],"but":[14],"challenging":[15],"research":[16],"topic":[17],"in":[18,92,133],"remote":[19,75,166],"sensing.":[20],"In":[21,109],"this":[22],"article,":[23],"we":[24,48],"propose":[25],"new":[27,51],"approach":[28],"to":[29,94,102,128,153,185],"exploit":[30],"complementarity":[32],"two":[34,135],"sources:":[36],"hyperspectral":[37],"images":[38],"(HSIs)":[39],"and":[40,43,55,71,80,89,97,101],"light":[41],"detection":[42],"ranging":[44],"(LiDAR)":[45],"data.":[46,77],"Specifically,":[47],"develop":[49],"dual-channel":[52,65,175],"spatial,":[53],"spectral":[54],"multiscale":[56,81,104],"attention":[57,82,117],"convolutional":[58],"long":[59],"short-term":[60],"memory":[61],"neural":[62],"network":[63],"(called":[64],"A<sup>3</sup>":[66],"CLNN)":[67],"for":[68,87,106],"feature":[69,99,181],"extraction":[70],"classification":[72,157,188],"multisource":[74,165],"sensing":[76,167],"Spatial,":[78],"spectral,":[79],"mechanisms":[83],"are":[84],"first":[85],"designed":[86,111,152],"HSI":[88],"LiDAR":[90],"order":[93],"learn":[95],"spectral-":[96],"spatial-enhanced":[98],"representations":[100],"represent":[103],"different":[107],"classes.":[108],"fusion":[112,124],"network,":[113],"novel":[115,147],"composite":[116],"learning":[118],"mechanism":[119],"(combined":[120],"with":[121],"three-level":[123],"strategy)":[125],"is":[126,151],"used":[127],"fully":[129],"integrate":[130],"features":[132],"these":[134],"sources.":[137],"Finally,":[138],"inspired":[139],"by":[140],"idea":[142],"transfer":[144],"learning,":[145],"stepwise":[148],"training":[149],"strategy":[150],"yield":[154],"final":[156],"result.":[158],"Our":[159],"experimental":[160],"results,":[161],"conducted":[162],"on":[163],"several":[164],"sets,":[169],"demonstrate":[170],"that":[171],"newly":[173],"proposed":[174],"A":[176],"<sup>3</sup>":[177],"CLNN":[178],"exhibits":[179],"better":[180],"representation":[182],"ability":[183],"(leading":[184],"more":[186],"competitive":[187],"performance)":[189],"than":[190],"other":[191],"state-of-the-art":[192],"methods.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":36},{"year":2024,"cited_by_count":38},{"year":2023,"cited_by_count":34},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":7}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}