{"id":"https://openalex.org/W4205102943","doi":"https://doi.org/10.1109/lgrs.2021.3139358","title":"Dual-Channel Convolution Network With Image-Based Global Learning Framework for Hyperspectral Image Classification","display_name":"Dual-Channel Convolution Network With Image-Based Global Learning Framework for Hyperspectral Image Classification","publication_year":2021,"publication_date":"2021-12-30","ids":{"openalex":"https://openalex.org/W4205102943","doi":"https://doi.org/10.1109/lgrs.2021.3139358"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2021.3139358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3139358","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5081712622","display_name":"Haoyang Yu","orcid":"https://orcid.org/0000-0002-4026-7450"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyang Yu","raw_affiliation_strings":["Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-4026-7450","affiliations":[{"raw_affiliation_string":"Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396842","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0002-0206-9381"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100742042","display_name":"Yao Liu","orcid":"https://orcid.org/0000-0003-1695-9956"},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210092591","display_name":"China Centre for Resources Satellite Data and Application","ror":"https://ror.org/00ft0fw96","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092591"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Liu","raw_affiliation_strings":["Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1695-9956","affiliations":[{"raw_affiliation_string":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing, China","institution_ids":["https://openalex.org/I211433327","https://openalex.org/I4210092591"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020896207","display_name":"Ke Zheng","orcid":"https://orcid.org/0000-0002-0108-0511"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Zheng","raw_affiliation_strings":["College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, China","Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0108-0511","affiliations":[{"raw_affiliation_string":"College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040597347","display_name":"Zhen Xu","orcid":"https://orcid.org/0000-0002-7201-3383"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Xu","raw_affiliation_strings":["Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102663415","display_name":"Chenchao Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210092591","display_name":"China Centre for Resources Satellite Data and Application","ror":"https://ror.org/00ft0fw96","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092591"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenchao Xiao","raw_affiliation_strings":["Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing, China","institution_ids":["https://openalex.org/I211433327","https://openalex.org/I4210092591"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.7259,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.93855567,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"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":0.9904000163078308,"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":0.9682999849319458,"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":0.8282189965248108},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7160722613334656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6914544105529785},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6861671805381775},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6502571105957031},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6264746189117432},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5829991102218628},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5334109663963318},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4892723262310028},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41613590717315674},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32753995060920715},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3018978238105774}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8282189965248108},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7160722613334656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6914544105529785},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6861671805381775},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6502571105957031},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6264746189117432},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5829991102218628},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5334109663963318},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4892723262310028},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41613590717315674},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32753995060920715},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3018978238105774},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2021.3139358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3139358","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2845203061","display_name":null,"funder_award_id":"42101350","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3946365887","display_name":null,"funder_award_id":"2020M680925","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G6854541950","display_name":null,"funder_award_id":"2021M693234","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G8588348077","display_name":null,"funder_award_id":"41901304","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2038386419","https://openalex.org/W2113513024","https://openalex.org/W2158400785","https://openalex.org/W2763731268","https://openalex.org/W2764276316","https://openalex.org/W2792332881","https://openalex.org/W2808098982","https://openalex.org/W3059552342","https://openalex.org/W3105357426","https://openalex.org/W3114720220","https://openalex.org/W3125860323","https://openalex.org/W3139578059","https://openalex.org/W3158390871","https://openalex.org/W3159815144"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440"],"abstract_inverted_index":{"Recently,":[0],"convolutional":[1,77],"neural":[2],"networks":[3],"(CNNs)":[4],"have":[5],"been":[6],"widely":[7],"applied":[8],"to":[9,15,66,83,110],"hyperspectral":[10,102],"image":[11],"(HSI)":[12],"classification":[13,26,82],"due":[14],"their":[16],"detailed":[17],"representation":[18],"of":[19,46,87,93,116],"features.":[20],"Nevertheless,":[21],"the":[22,44,85,88],"current":[23],"CNN-based":[24],"HSI":[25,67,81,122],"methods":[27,35,113],"mainly":[28],"follow":[29],"a":[30,52,75],"patch-based":[31],"learning":[32,38,62],"framework.":[33],"These":[34],"are":[36],"nonglobal":[37],"methods,":[39],"which":[40],"not":[41],"only":[42],"limit":[43],"use":[45],"global":[47,61,89],"information":[48,92],"but":[49],"also":[50],"require":[51],"high":[53],"computational":[54],"cost.":[55],"In":[56],"this":[57,71],"letter,":[58],"an":[59],"image-based":[60],"framework":[63],"is":[64,108],"introduced":[65],"classification.":[68,123],"Based":[69],"on":[70,99],"framework,":[72],"we":[73],"propose":[74],"dual-channel":[76],"network":[78],"(DCCN)":[79],"for":[80,121],"maximize":[84],"exploitation":[86],"and":[90,119],"multiscale":[91],"HSI.":[94],"The":[95],"experimental":[96],"results":[97],"conducted":[98],"two":[100],"real":[101],"datasets":[103],"indicate":[104],"that":[105],"our":[106],"method":[107],"superior":[109],"other":[111],"related":[112],"in":[114],"terms":[115],"both":[117],"efficiency":[118],"accuracy":[120]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":15}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
