{"id":"https://openalex.org/W4220844146","doi":"https://doi.org/10.3390/rs14071652","title":"Multiscale Feature Aggregation Capsule Neural Network for Hyperspectral Remote Sensing Image Classification","display_name":"Multiscale Feature Aggregation Capsule Neural Network for Hyperspectral Remote Sensing Image Classification","publication_year":2022,"publication_date":"2022-03-30","ids":{"openalex":"https://openalex.org/W4220844146","doi":"https://doi.org/10.3390/rs14071652"},"language":"en","primary_location":{"id":"doi:10.3390/rs14071652","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14071652","pdf_url":"https://www.mdpi.com/2072-4292/14/7/1652/pdf?version=1648628354","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/2072-4292/14/7/1652/pdf?version=1648628354","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045348308","display_name":"Runmin Lei","orcid":"https://orcid.org/0000-0002-2686-4208"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runmin Lei","raw_affiliation_strings":["School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":"https://orcid.org/0000-0002-2686-4208","affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056719441","display_name":"Chunju Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunju Zhang","raw_affiliation_strings":["School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445979","display_name":"Xueying Zhang","orcid":"https://orcid.org/0000-0003-1364-4385"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xueying Zhang","raw_affiliation_strings":["Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing 210023, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing 210023, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058811596","display_name":"Jianwei Huang","orcid":"https://orcid.org/0000-0002-0207-8800"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwei Huang","raw_affiliation_strings":["School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":"https://orcid.org/0000-0002-0207-8800","affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076691929","display_name":"Zhenxuan Li","orcid":"https://orcid.org/0000-0002-0528-8328"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenxuan Li","raw_affiliation_strings":["School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":"https://orcid.org/0000-0002-0528-8328","affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071484374","display_name":"Wencong Liu","orcid":"https://orcid.org/0000-0001-6918-9831"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wencong Liu","raw_affiliation_strings":["School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059651484","display_name":"Hao Cui","orcid":"https://orcid.org/0000-0002-9417-5068"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Cui","raw_affiliation_strings":["School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5056719441"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.5818,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.845502,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"14","issue":"7","first_page":"1652","last_page":"1652"},"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":0.9980000257492065,"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":0.9871000051498413,"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":0.776059091091156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7476209998130798},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6861687898635864},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6623047590255737},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5931863784790039},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5844793915748596},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5787490606307983},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5310514569282532},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5228462815284729},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4657173156738281},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4566792845726013},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44804513454437256},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12190264463424683}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.776059091091156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7476209998130798},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6861687898635864},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6623047590255737},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5931863784790039},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5844793915748596},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5787490606307983},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5310514569282532},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5228462815284729},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4657173156738281},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4566792845726013},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44804513454437256},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12190264463424683},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14071652","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14071652","pdf_url":"https://www.mdpi.com/2072-4292/14/7/1652/pdf?version=1648628354","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:8fa428fe91794e688783fbe026d4dee2","is_oa":true,"landing_page_url":"https://doaj.org/article/8fa428fe91794e688783fbe026d4dee2","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 14, Iss 7, p 1652 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/7/1652/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14071652","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 7; Pages: 1652","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14071652","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14071652","pdf_url":"https://www.mdpi.com/2072-4292/14/7/1652/pdf?version=1648628354","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","display_name":"Reduced inequalities","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G32458438","display_name":null,"funder_award_id":"JZ2021HGTB0088","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3789180131","display_name":null,"funder_award_id":"41971337","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5306819764","display_name":null,"funder_award_id":"42171453","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4220844146.pdf","grobid_xml":"https://content.openalex.org/works/W4220844146.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1998030312","https://openalex.org/W2029316659","https://openalex.org/W2039409148","https://openalex.org/W2090424610","https://openalex.org/W2098057602","https://openalex.org/W2101711129","https://openalex.org/W2136251662","https://openalex.org/W2142009246","https://openalex.org/W2144966944","https://openalex.org/W2194775991","https://openalex.org/W2257669061","https://openalex.org/W2276858186","https://openalex.org/W2336549754","https://openalex.org/W2500751094","https://openalex.org/W2548791488","https://openalex.org/W2558391528","https://openalex.org/W2572303978","https://openalex.org/W2587790406","https://openalex.org/W2620547787","https://openalex.org/W2743255627","https://openalex.org/W2752782242","https://openalex.org/W2764276316","https://openalex.org/W2767651786","https://openalex.org/W2782420567","https://openalex.org/W2783443613","https://openalex.org/W2791006446","https://openalex.org/W2792332881","https://openalex.org/W2888119354","https://openalex.org/W2889943009","https://openalex.org/W2890182766","https://openalex.org/W2892075618","https://openalex.org/W2898381489","https://openalex.org/W2900875621","https://openalex.org/W2907100627","https://openalex.org/W2911968856","https://openalex.org/W2912371366","https://openalex.org/W2943270518","https://openalex.org/W2944413439","https://openalex.org/W2979923697","https://openalex.org/W2988188869","https://openalex.org/W2992919850","https://openalex.org/W2998142089","https://openalex.org/W3004480865","https://openalex.org/W3010700973","https://openalex.org/W3031768327","https://openalex.org/W3034100957","https://openalex.org/W3046007115","https://openalex.org/W3049655825","https://openalex.org/W3081861870","https://openalex.org/W3120367458","https://openalex.org/W3198812651","https://openalex.org/W4240485910","https://openalex.org/W4320339642","https://openalex.org/W6769481713"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3204184292","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W3176564347","https://openalex.org/W2019190440"],"abstract_inverted_index":{"Models":[0],"based":[1,91,136],"on":[2,92,137,226],"capsule":[3,87,132,140,199],"neural":[4,88],"network":[5,89,154],"(CapsNet),":[6],"a":[7,46,83,166,186,208],"novel":[8],"deep":[9,57,120,197],"learning":[10,58],"method,":[11],"have":[12],"recently":[13],"made":[14],"great":[15],"achievements":[16],"in":[17,37,49,75,162,172],"hyperspectral":[18],"remote":[19],"sensing":[20],"image":[21],"(HSI)":[22],"classification":[23,78,220],"due":[24],"to":[25,29,110,148,178,203,241],"their":[26],"excellent":[27],"ability":[28],"implicitly":[30],"model":[31,116,206],"the":[32,40,53,62,71,76,95,150,153,157,173,205,218,234],"spatial":[33,108],"relationship":[34],"knowledge":[35],"embedded":[36],"HSIs.":[38],"However,":[39],"number":[41],"of":[42,55,64,73,97,131,152,176,211,222,243],"labeled":[43,66,159],"samples":[44,67],"is":[45,170,201],"common":[47],"bottleneck":[48],"HSI":[50,77,163,219,230],"classification,":[51],"limiting":[52],"performance":[54],"these":[56],"models.":[59],"To":[60],"alleviate":[61],"problem":[63,161],"limited":[65,158],"and":[68,106,114,143,155,215],"further":[69,216],"explore":[70],"potential":[72],"CapsNet":[74,93],"field,":[79],"this":[80],"study":[81],"proposes":[82],"multiscale":[84,112],"feature":[85,181],"aggregation":[86],"(MS-CapsNet)":[90],"via":[94],"implementation":[96],"two":[98,129,194],"branches":[99],"that":[100,190,233],"simultaneously":[101],"extract":[102],"spectral,":[103],"local":[104],"spatial,":[105],"global":[107],"features":[109,113,121],"integrate":[111],"improve":[115,217],"robustness.":[117],"Furthermore,":[118],"because":[119],"are":[122,146],"generally":[123],"more":[124],"discriminative":[125],"than":[126],"shallow":[127,174],"features,":[128],"kinds":[130],"residual":[133,144],"(CapsRES)":[134],"blocks":[135],"3D":[138],"convolutional":[139,198],"(3D-ConvCaps)":[141],"layers":[142,175],"connections":[145],"proposed":[147,235],"increase":[149],"depth":[151],"solve":[156],"sample":[160],"classification.":[164],"Moreover,":[165],"squeeze-and-excitation":[167],"(SE)":[168],"block":[169],"introduced":[171,202],"MS-CapsNet":[177],"enhance":[179],"its":[180],"extraction":[182],"ability.":[183],"In":[184],"addition,":[185],"reasonable":[187],"initialization":[188],"strategy":[189],"transfers":[191],"parameters":[192,214],"from":[193],"well-designed,":[195],"pretrained":[196],"networks":[200],"help":[204],"find":[207],"good":[209],"set":[210],"initializing":[212],"weight":[213],"accuracy":[221],"MS-CapsNet.":[223],"Experimental":[224],"results":[225,239],"four":[227],"widely":[228],"used":[229],"datasets":[231],"demonstrate":[232],"method":[236],"can":[237],"provide":[238],"comparable":[240],"those":[242],"state-of-the-art":[244],"methods.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2022-04-03T00:00:00"}
