{"id":"https://openalex.org/W4312811001","doi":"https://doi.org/10.1109/igarss46834.2022.9884905","title":"Residual Dense Asymmetric Convolutional Neural Network for Hyperspectral Image Classification","display_name":"Residual Dense Asymmetric Convolutional Neural Network for Hyperspectral Image Classification","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4312811001","doi":"https://doi.org/10.1109/igarss46834.2022.9884905"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9884905","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884905","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5061913887","display_name":"Zhe Meng","orcid":"https://orcid.org/0000-0002-2364-2749"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Meng","raw_affiliation_strings":["School of Communications and Information Engineering (School of Artificial Intelligence), School of Cyberspace Security, Xi’ an University of Posts and Telecommunications,Xi'an,China,710121"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering (School of Artificial Intelligence), School of Cyberspace Security, Xi’ an University of Posts and Telecommunications,Xi'an,China,710121","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038759055","display_name":"Junjie Zhang","orcid":"https://orcid.org/0000-0002-0895-3127"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Zhang","raw_affiliation_strings":["School of Communications and Information Engineering (School of Artificial Intelligence), School of Cyberspace Security, Xi’ an University of Posts and Telecommunications,Xi'an,China,710121"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering (School of Artificial Intelligence), School of Cyberspace Security, Xi’ an University of Posts and Telecommunications,Xi'an,China,710121","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100706940","display_name":"Feng Zhao","orcid":"https://orcid.org/0000-0002-0323-9573"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Zhao","raw_affiliation_strings":["School of Communications and Information Engineering (School of Artificial Intelligence), School of Cyberspace Security, Xi’ an University of Posts and Telecommunications,Xi'an,China,710121"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering (School of Artificial Intelligence), School of Cyberspace Security, Xi’ an University of Posts and Telecommunications,Xi'an,China,710121","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005672975","display_name":"Hanqiang Liu","orcid":"https://orcid.org/0000-0001-8774-8625"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanqiang Liu","raw_affiliation_strings":["School of Computer Science, Shaanxi Normal University,Xi'an,China,710119"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Shaanxi Normal University,Xi'an,China,710119","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081366160","display_name":"Zhenhui Chang","orcid":"https://orcid.org/0000-0001-5895-5916"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhui Chang","raw_affiliation_strings":["School of Communications and Information Engineering (School of Artificial Intelligence), School of Cyberspace Security, Xi’ an University of Posts and Telecommunications,Xi'an,China,710121"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering (School of Artificial Intelligence), School of Cyberspace Security, Xi’ an University of Posts and Telecommunications,Xi'an,China,710121","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9142,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.96096377,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3159","last_page":"3162"},"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":0.994700014591217,"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":0.972000002861023,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.814108669757843},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7852458953857422},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7425850629806519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7055940628051758},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.688586413860321},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6840424537658691},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6249638795852661},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5409172177314758},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.519707977771759},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5144129395484924},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4949130415916443},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.4419119656085968},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4369540214538574},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4163256883621216},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22039389610290527},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16237887740135193},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1529165804386139},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.1379179060459137}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.814108669757843},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7852458953857422},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7425850629806519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7055940628051758},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.688586413860321},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6840424537658691},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6249638795852661},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5409172177314758},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.519707977771759},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5144129395484924},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4949130415916443},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.4419119656085968},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4369540214538574},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4163256883621216},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22039389610290527},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16237887740135193},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1529165804386139},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.1379179060459137},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9884905","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9884905","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3385537974","display_name":null,"funder_award_id":"62071379,61901365,61571361","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7109631932","display_name":null,"funder_award_id":"GK202103085","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8969952975","display_name":null,"funder_award_id":"xyt2016-0l","funder_id":"https://openalex.org/F4320325367","funder_display_name":"Xi'an University of Posts and Telecommunications"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325367","display_name":"Xi'an University of Posts and Telecommunications","ror":null},{"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":11,"referenced_works":["https://openalex.org/W2572303978","https://openalex.org/W2614166664","https://openalex.org/W2764276316","https://openalex.org/W2888119354","https://openalex.org/W2892075618","https://openalex.org/W2969937244","https://openalex.org/W2981609437","https://openalex.org/W2989697276","https://openalex.org/W3003289138","https://openalex.org/W3196510907","https://openalex.org/W6766837696"],"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/W2761785940","https://openalex.org/W2129933262"],"abstract_inverted_index":{"Recently,":[0],"convolutional":[1,40,59,92,99],"neural":[2],"networks":[3],"(CNNs)":[4],"show":[5,114],"excellent":[6],"performance":[7,120],"on":[8,109],"the":[9,33,64,67,71,89,97,123],"hyperspectral":[10,86,112],"image":[11],"(HSI)":[12],"classification":[13,45,119],"tasks.":[14],"However,":[15],"traditional":[16],"CNNs":[17],"usually":[18],"have":[19],"insufficient":[20],"feature":[21,75],"discrimination":[22],"and":[23,80],"a":[24,36,54],"large":[25],"number":[26],"of":[27,66,78],"network":[28,41],"parameters.":[29,105],"In":[30],"response":[31],"to":[32,61,83],"above":[34],"problems,":[35],"residual":[37,56],"dense":[38,57],"asymmetric":[39,58,98],"(RDACN)":[42],"for":[43],"HSI":[44],"is":[46,94],"proposed":[47],"in":[48],"this":[49],"paper.":[50],"Firstly,":[51],"we":[52],"de-sign":[53],"novel":[55],"block":[60,72],"effectively":[62],"leverage":[63],"information":[65],"previous":[68],"layers.":[69],"Moreover,":[70],"adopts":[73],"two":[74],"fusion":[76],"methods":[77],"addition":[79],"channel":[81],"stacking":[82],"capture":[84],"discriminative":[85],"feature.":[87],"Secondly,":[88],"ordinary":[90],"square":[91],"kernel":[93],"replaced":[95],"with":[96,122],"kernels,":[100],"which":[101],"can":[102],"reduce":[103],"CNN":[104],"Finally,":[106],"experimental":[107],"results":[108],"three":[110],"well-known":[111],"datasets":[113],"that":[115],"RDACN":[116],"achieves":[117],"competitive":[118],"compared":[121],"state-of-the-art":[124],"CNNs.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}