{"id":"https://openalex.org/W4399939472","doi":"https://doi.org/10.1109/tgrs.2024.3418583","title":"Dual-Branch Subpixel-Guided Network for Hyperspectral Image Classification","display_name":"Dual-Branch Subpixel-Guided Network for Hyperspectral Image Classification","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399939472","doi":"https://doi.org/10.1109/tgrs.2024.3418583"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3418583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3418583","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2412.03893","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023381631","display_name":"Zhu Han","orcid":"https://orcid.org/0000-0002-8602-864X"},"institutions":[{"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":true,"raw_author_name":"Zhu Han","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, and the International Research Center of Big Data for Sustainable Development Goals, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, and the International Research Center of Big Data for Sustainable Development Goals, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jin Yang","orcid":"https://orcid.org/0009-0003-2177-7695"},"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/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":"Jin Yang","raw_affiliation_strings":["Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066378186","display_name":"Lianru Gao","orcid":"https://orcid.org/0000-0003-3888-8124"},"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/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":"Lianru Gao","raw_affiliation_strings":["Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015515281","display_name":"Zhiqiang Zeng","orcid":"https://orcid.org/0000-0002-6615-9626"},"institutions":[{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Zeng","raw_affiliation_strings":["Beijing Institute of Remote Sensing Equipment, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Remote Sensing Equipment, Beijing, China","institution_ids":["https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389658","display_name":"Bing Zhang","orcid":"https://orcid.org/0000-0001-7311-9844"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Zhang","raw_affiliation_strings":["College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"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/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":"Jocelyn Chanussot","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5023381631"],"corresponding_institution_ids":["https://openalex.org/I4210137199"],"apc_list":null,"apc_paid":null,"fwci":12.8554,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.9891146,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"13"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9952999949455261,"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":0.9926999807357788,"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":0.9241412878036499},{"id":"https://openalex.org/keywords/subpixel-rendering","display_name":"Subpixel rendering","score":0.8230901956558228},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5883307456970215},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5353653430938721},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5049124360084534},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4576683044433594},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.45491480827331543},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43093040585517883},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.41865187883377075},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4058331847190857},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.38388490676879883},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3688323199748993},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.28089410066604614}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9241412878036499},{"id":"https://openalex.org/C68516990","wikidata":"https://www.wikidata.org/wiki/Q452912","display_name":"Subpixel rendering","level":3,"score":0.8230901956558228},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5883307456970215},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5353653430938721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5049124360084534},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4576683044433594},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.45491480827331543},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43093040585517883},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.41865187883377075},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4058331847190857},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.38388490676879883},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3688323199748993},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.28089410066604614},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2024.3418583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3418583","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2412.03893","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.03893","pdf_url":"https://arxiv.org/pdf/2412.03893","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:2412.03893","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.03893","pdf_url":"https://arxiv.org/pdf/2412.03893","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/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4355221328","display_name":null,"funder_award_id":"42325104","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5477570599","display_name":null,"funder_award_id":"621611603","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7092763903","display_name":null,"funder_award_id":"62161160336","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"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4399939472.pdf"},"referenced_works_count":81,"referenced_works":["https://openalex.org/W1957094454","https://openalex.org/W1963659868","https://openalex.org/W1973450996","https://openalex.org/W1997718749","https://openalex.org/W2005818237","https://openalex.org/W2011315899","https://openalex.org/W2019274094","https://openalex.org/W2022470997","https://openalex.org/W2085529604","https://openalex.org/W2087263574","https://openalex.org/W2088259770","https://openalex.org/W2127495569","https://openalex.org/W2143500192","https://openalex.org/W2151665594","https://openalex.org/W2159070926","https://openalex.org/W2160675285","https://openalex.org/W2161815745","https://openalex.org/W2187089797","https://openalex.org/W2500751094","https://openalex.org/W2558098092","https://openalex.org/W2614256707","https://openalex.org/W2754507318","https://openalex.org/W2767805377","https://openalex.org/W2789643644","https://openalex.org/W2811009023","https://openalex.org/W2811355488","https://openalex.org/W2911419410","https://openalex.org/W2921511952","https://openalex.org/W2942454403","https://openalex.org/W2943325261","https://openalex.org/W2949351478","https://openalex.org/W2991494819","https://openalex.org/W2991616716","https://openalex.org/W2998142089","https://openalex.org/W2998823444","https://openalex.org/W3005360455","https://openalex.org/W3011424859","https://openalex.org/W3024007459","https://openalex.org/W3028000844","https://openalex.org/W3047443805","https://openalex.org/W3047895866","https://openalex.org/W3048051136","https://openalex.org/W3088162569","https://openalex.org/W3103695279","https://openalex.org/W3103750833","https://openalex.org/W3103753223","https://openalex.org/W3111935347","https://openalex.org/W3122463936","https://openalex.org/W3128776197","https://openalex.org/W3133055443","https://openalex.org/W3137191419","https://openalex.org/W3138637597","https://openalex.org/W3154556605","https://openalex.org/W3167109952","https://openalex.org/W3181729304","https://openalex.org/W3196539133","https://openalex.org/W3214821343","https://openalex.org/W4206727312","https://openalex.org/W4210541032","https://openalex.org/W4210794570","https://openalex.org/W4214854488","https://openalex.org/W4226070402","https://openalex.org/W4233760599","https://openalex.org/W4240485910","https://openalex.org/W4285207472","https://openalex.org/W4285223668","https://openalex.org/W4285310237","https://openalex.org/W4292826027","https://openalex.org/W4312659060","https://openalex.org/W4320339642","https://openalex.org/W4321380750","https://openalex.org/W4385245566","https://openalex.org/W4385413338","https://openalex.org/W4386266673","https://openalex.org/W4388750241","https://openalex.org/W4388988031","https://openalex.org/W4390494483","https://openalex.org/W4390703889","https://openalex.org/W4392940549","https://openalex.org/W4394938955","https://openalex.org/W4396712667"],"related_works":["https://openalex.org/W2369528593","https://openalex.org/W2385629811","https://openalex.org/W2638735979","https://openalex.org/W2111510641","https://openalex.org/W2386795888","https://openalex.org/W1968995436","https://openalex.org/W2120293966","https://openalex.org/W2142380919","https://openalex.org/W2076134148","https://openalex.org/W2111946936"],"abstract_inverted_index":{"Deep":[0],"learning":[1,17],"(DL)":[2],"has":[3],"been":[4],"widely":[5],"applied":[6],"to":[7,13,89,113,129,174],"hyperspectral":[8],"image":[9],"(HSI)":[10],"classification,":[11,70],"owing":[12],"its":[14],"promising":[15],"feature":[16],"and":[18,38,78,104,136,153],"representation":[19],"capabilities.":[20],"However,":[21],"limited":[22],"by":[23,82],"the":[24,49,151,175],"spatial":[25,39],"resolution":[26],"of":[27,51,96,155],"sensors,":[28],"existing":[29],"DL-based":[30,160],"classification":[31,91,162],"approaches":[32],"mainly":[33],"focus":[34],"on":[35,146],"pixel-level":[36],"spectral":[37],"information":[40,77,132],"extraction":[41],"through":[42],"complex":[43],"network":[44,67],"architecture":[45,88],"design":[46],"while":[47],"ignoring":[48],"existence":[50],"mixed":[52],"pixels":[53],"in":[54,109],"actual":[55],"scenarios.":[56],"To":[57],"tackle":[58],"this":[59],"difficulty,":[60],"we":[61],"propose":[62],"a":[63,84],"novel":[64],"dual-branch":[65],"subpixel-guided":[66],"for":[68,119],"HSI":[69,161],"called":[71],"DSNet,":[72],"which":[73],"automatically":[74],"integrates":[75],"subpixel":[76,124,137],"convolutional":[79],"class":[80,120],"features":[81],"introducing":[83],"deep":[85],"autoencoder":[86],"unmixing":[87],"enhance":[90],"performance.":[92],"DSNet":[93,156],"is":[94,127],"capable":[95],"fully":[97],"considering":[98],"physically":[99],"nonlinear":[100],"properties":[101],"within":[102],"subpixels":[103],"adaptively":[105],"generating":[106],"diagnostic":[107],"abundances":[108],"an":[110],"unsupervised":[111],"manner":[112],"achieve":[114],"more":[115],"reliable":[116],"decision":[117],"boundaries":[118],"label":[121],"distributions.":[122],"The":[123,164],"fusion":[125,133],"module":[126],"designed":[128],"ensure":[130],"high-quality":[131],"across":[134],"pixel":[135],"features,":[138],"further":[139],"promoting":[140],"stable":[141],"joint":[142],"classification.":[143],"Experimental":[144],"results":[145],"three":[147],"benchmark":[148],"datasets":[149],"demonstrate":[150],"effectiveness":[152],"superiority":[154],"compared":[157],"with":[158],"state-of-the-art":[159],"approaches.":[163],"codes":[165],"will":[166],"be":[167],"available":[168],"at":[169],"<uri":[170],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[171],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/hanzhu97702/DSNet</uri>,":[172],"contributing":[173],"remote":[176],"sensing":[177],"community.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":8}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
