{"id":"https://openalex.org/W4402259905","doi":"https://doi.org/10.1109/igarss53475.2024.10642910","title":"CNN and Transformer Hybrid Network for Hyperspectral Image Classification","display_name":"CNN and Transformer Hybrid Network for Hyperspectral Image Classification","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402259905","doi":"https://doi.org/10.1109/igarss53475.2024.10642910"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10642910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10642910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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/A5101671584","display_name":"Zhaobin Wang","orcid":"https://orcid.org/0000-0002-7059-9907"},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhaobin Wang","raw_affiliation_strings":["Lanzhou University,School of Information Science and Engineering,Lanzhou,China,730000"],"affiliations":[{"raw_affiliation_string":"Lanzhou University,School of Information Science and Engineering,Lanzhou,China,730000","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101759398","display_name":"Yan Li","orcid":"https://orcid.org/0000-0003-1882-3331"},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["Lanzhou University,School of Information Science and Engineering,Lanzhou,China,730000"],"affiliations":[{"raw_affiliation_string":"Lanzhou University,School of Information Science and Engineering,Lanzhou,China,730000","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101287193","display_name":"Zhongxin Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongxin Cheng","raw_affiliation_strings":["Lanzhou University,School of Information Science and Engineering,Lanzhou,China,730000"],"affiliations":[{"raw_affiliation_string":"Lanzhou University,School of Information Science and Engineering,Lanzhou,China,730000","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077295889","display_name":"Yaonan Zhang","orcid":"https://orcid.org/0000-0001-8905-9006"},"institutions":[{"id":"https://openalex.org/I4210106526","display_name":"Northwest Institute of Eco-Environment and Resources","ror":"https://ror.org/01jz1e142","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210106526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaonan Zhang","raw_affiliation_strings":["Northwest Institute of Eco-Environment and Resources, CAS,Lanzhou,China,730000"],"affiliations":[{"raw_affiliation_string":"Northwest Institute of Eco-Environment and Resources, CAS,Lanzhou,China,730000","institution_ids":["https://openalex.org/I4210106526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101671584"],"corresponding_institution_ids":["https://openalex.org/I76214153"],"apc_list":null,"apc_paid":null,"fwci":1.0148,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.79742173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"9091","last_page":"9095"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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":0.9997000098228455,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9919000267982483,"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":0.9883999824523926,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8819458484649658},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.634324312210083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5824854373931885},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5178661346435547},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5085936784744263},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3208048939704895},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1245744526386261},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.08216115832328796},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.06245994567871094}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8819458484649658},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.634324312210083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5824854373931885},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5178661346435547},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5085936784744263},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3208048939704895},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1245744526386261},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.08216115832328796},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.06245994567871094}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10642910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10642910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1976027628","https://openalex.org/W2113464037","https://openalex.org/W2136251662","https://openalex.org/W2150871663","https://openalex.org/W2164448908","https://openalex.org/W2221243399","https://openalex.org/W2805177060","https://openalex.org/W2907100627","https://openalex.org/W2917189553","https://openalex.org/W2963037989","https://openalex.org/W2977002487","https://openalex.org/W3094502228","https://openalex.org/W3128776197","https://openalex.org/W3172304795","https://openalex.org/W3214821343","https://openalex.org/W4210794570","https://openalex.org/W4246193833","https://openalex.org/W4285204365","https://openalex.org/W4385245566","https://openalex.org/W6635815790","https://openalex.org/W6784333009"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2772917594","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"Hyperspectral":[0],"images":[1],"(HSIs)":[2],"contain":[3],"a":[4,82],"wealth":[5],"of":[6,15,28,74,123,130,154,167],"information":[7],"and":[8,19,53,88,98,133,148],"have":[9],"important":[10],"applications":[11],"in":[12,39,77],"the":[13,54,71,95,105,112,121,124,140,164],"fields":[14],"military,":[16],"agriculture,":[17],"medicine":[18],"et":[20],"al.":[21],"The":[22,59],"excellent":[23],"local":[24],"feature":[25,108],"representation":[26],"ability":[27,46,61],"convolutional":[29,114],"neural":[30],"network":[31,84,125],"(CNN)":[32],"makes":[33],"it":[34],"achieve":[35],"good":[36],"classification":[37,42,165],"results":[38,156],"hyperspectral":[40],"image":[41],"tasks,":[43],"but":[44],"its":[45],"to":[47,62,119,126,145],"capture":[48],"global":[49,64,150],"features":[50,65,100],"is":[51,57,117,143],"limited":[52],"computational":[55],"cost":[56],"high.":[58],"Transformer\u2019s":[60],"represent":[63,147],"can":[66],"largely":[67],"make":[68],"up":[69],"for":[70,91],"above":[72],"shortcomings":[73],"CNNs.":[75],"Therefore,":[76],"this":[78],"paper,":[79],"we":[80],"propose":[81],"hybrid":[83],"based":[85],"on":[86,157],"CNN":[87],"transformer":[89,141],"(CTHN)":[90],"HSI":[92],"classification.":[93],"Firstly,":[94],"multi-scale":[96,106],"spectral":[97],"spatial":[99,137],"were":[101],"preliminarily":[102],"extracted":[103],"through":[104],"spectral-spatial":[107],"extraction":[109],"module.":[110],"Then,":[111],"deformable":[113],"residual":[115],"module":[116,142],"introduced":[118],"enhance":[120],"adaptability":[122],"various":[127],"complex":[128,136],"shapes":[129],"ground":[131],"objects,":[132],"further":[134],"learn":[135,149],"information.":[138],"Finally,":[139],"used":[144],"deeply":[146],"features.":[151],"A":[152],"series":[153],"experimental":[155],"three":[158],"publicly":[159],"available":[160],"datasets":[161],"show":[162],"that":[163],"performance":[166],"CTHN":[168],"outperforms":[169],"several":[170],"state-of-the-art":[171],"comparison":[172],"algorithms.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
