{"id":"https://openalex.org/W4399432959","doi":"https://doi.org/10.3390/rs16122051","title":"Hyperspectral Image Classification Based on Double-Branch Multi-Scale Dual-Attention Network","display_name":"Hyperspectral Image Classification Based on Double-Branch Multi-Scale Dual-Attention Network","publication_year":2024,"publication_date":"2024-06-07","ids":{"openalex":"https://openalex.org/W4399432959","doi":"https://doi.org/10.3390/rs16122051"},"language":"en","primary_location":{"id":"doi:10.3390/rs16122051","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16122051","pdf_url":"https://www.mdpi.com/2072-4292/16/12/2051/pdf?version=1717749953","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/2072-4292/16/12/2051/pdf?version=1717749953","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114269740","display_name":"Heng Zhang","orcid":"https://orcid.org/0009-0001-3127-7956"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Zhang","raw_affiliation_strings":["School of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077996365","display_name":"Hanhu Liu","orcid":"https://orcid.org/0000-0002-2928-7995"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hanhu Liu","raw_affiliation_strings":["School of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074023635","display_name":"Ronghao Yang","orcid":"https://orcid.org/0000-0002-3394-090X"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghao Yang","raw_affiliation_strings":["School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100726417","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0003-1813-0551"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111223031","display_name":"Qingqu Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingqu Luo","raw_affiliation_strings":["School of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047457782","display_name":"C Tu","orcid":null},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changda Tu","raw_affiliation_strings":["School of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"],"affiliations":[{"raw_affiliation_string":"School of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China","institution_ids":["https://openalex.org/I31595395"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5077996365"],"corresponding_institution_ids":["https://openalex.org/I31595395"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.1273,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.94470326,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"16","issue":"12","first_page":"2051","last_page":"2051"},"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9868999719619751,"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":0.889677882194519},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7163827419281006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5938770174980164},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5872798562049866},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5790759325027466},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4769786298274994},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.46268004179000854},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.44150111079216003},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40376681089401245},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19503289461135864},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15148481726646423},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07639798521995544},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07436677813529968}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.889677882194519},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7163827419281006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5938770174980164},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5872798562049866},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5790759325027466},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4769786298274994},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.46268004179000854},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.44150111079216003},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40376681089401245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19503289461135864},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15148481726646423},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07639798521995544},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07436677813529968},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs16122051","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16122051","pdf_url":"https://www.mdpi.com/2072-4292/16/12/2051/pdf?version=1717749953","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:d6ac3c6fcee44187ad66a712d820ac95","is_oa":true,"landing_page_url":"https://doaj.org/article/d6ac3c6fcee44187ad66a712d820ac95","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 16, Iss 12, p 2051 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16122051","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16122051","pdf_url":"https://www.mdpi.com/2072-4292/16/12/2051/pdf?version=1717749953","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399432959.pdf"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W2058795991","https://openalex.org/W2113464037","https://openalex.org/W2136251662","https://openalex.org/W2194775991","https://openalex.org/W2396056163","https://openalex.org/W2614256707","https://openalex.org/W2764276316","https://openalex.org/W2767805377","https://openalex.org/W2792332881","https://openalex.org/W2822065499","https://openalex.org/W2910791660","https://openalex.org/W2942170965","https://openalex.org/W2948157022","https://openalex.org/W2955058313","https://openalex.org/W2961988411","https://openalex.org/W2963446712","https://openalex.org/W2992027343","https://openalex.org/W2999157894","https://openalex.org/W3002734626","https://openalex.org/W3005414792","https://openalex.org/W3011645114","https://openalex.org/W3043181422","https://openalex.org/W3102274762","https://openalex.org/W3103753223","https://openalex.org/W3111935347","https://openalex.org/W3123794525","https://openalex.org/W3140678646","https://openalex.org/W3153882363","https://openalex.org/W3165982433","https://openalex.org/W3191600511","https://openalex.org/W3192905226","https://openalex.org/W3192932942","https://openalex.org/W3214821343","https://openalex.org/W4206462182","https://openalex.org/W4207037158","https://openalex.org/W4225712758","https://openalex.org/W4281568429","https://openalex.org/W4285262969","https://openalex.org/W4285303509","https://openalex.org/W4292691763","https://openalex.org/W4311532677","https://openalex.org/W4312743284","https://openalex.org/W4312789082","https://openalex.org/W4312846227","https://openalex.org/W4313160444","https://openalex.org/W4317738525","https://openalex.org/W4378082492","https://openalex.org/W4380680196","https://openalex.org/W4385399695","https://openalex.org/W4385422088","https://openalex.org/W4385529325","https://openalex.org/W4386634608","https://openalex.org/W4389352598","https://openalex.org/W4389776891","https://openalex.org/W4390659015","https://openalex.org/W4390660108","https://openalex.org/W4391806825","https://openalex.org/W6677065643","https://openalex.org/W6793601869","https://openalex.org/W6795590120","https://openalex.org/W6799984494","https://openalex.org/W6839363971","https://openalex.org/W6861577408"],"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/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440","https://openalex.org/W2967006609"],"abstract_inverted_index":{"Although":[0],"extensive":[1],"research":[2],"shows":[3],"that":[4,59,152],"CNNs":[5],"achieve":[6],"good":[7],"classification":[8,43,158],"results":[9,139],"in":[10,136],"HSI":[11],"classification,":[12],"they":[13],"still":[14],"struggle":[15],"to":[16,113,126,165],"effectively":[17],"extract":[18,89],"spectral":[19,62,76,93],"sequence":[20],"information":[21,65,94,115],"from":[22,66,95],"HSIs.":[23],"Additionally,":[24,105],"the":[25,30,37,128,141,153],"high-dimensional":[26,90],"features":[27],"of":[28,33,84,132],"HSIs,":[29,96],"limited":[31,99],"number":[32],"labeled":[34,100],"samples,":[35],"and":[36,63,68,91,102,130,146,160],"common":[38],"sample":[39],"imbalance":[40],"significantly":[41],"restrict":[42],"performance":[44,159],"improvement.":[45],"To":[46],"address":[47],"these":[48],"issues,":[49],"this":[50,106,118],"article":[51,107,119],"proposes":[52],"a":[53,81,109,121],"double-branch":[54],"multi-scale":[55,75],"dual-attention":[56],"(DBMSDA)":[57],"network":[58],"fully":[60,88],"extracts":[61],"spatial":[64],"HSIs":[67],"fuses":[69],"them":[70],"for":[71],"classification.":[72],"The":[73],"designed":[74],"residual":[77],"self-attention":[78],"(MSeRA),":[79],"as":[80],"fundamental":[82],"component":[83],"dense":[85],"connections,":[86],"can":[87],"intricate":[92],"even":[97],"with":[98],"samples":[101],"imbalanced":[103],"distributions.":[104],"adopts":[108],"dataset":[110,125,145],"partitioning":[111],"strategy":[112],"prevent":[114],"leakage.":[116],"Finally,":[117],"introduces":[120],"hyperspectral":[122,144],"geological":[123,142],"lithology":[124,143],"evaluate":[127],"accuracy":[129],"applicability":[131],"deep":[133],"learning":[134],"methods":[135],"geology.":[137],"Experimental":[138],"on":[140],"three":[147],"other":[148],"public":[149],"datasets":[150],"demonstrate":[151],"DBMSDA":[154],"method":[155],"exhibits":[156],"superior":[157],"robust":[161],"generalization":[162],"ability":[163],"compared":[164],"existing":[166],"methods.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}