{"id":"https://openalex.org/W4285303509","doi":"https://doi.org/10.1109/tgrs.2022.3186400","title":"MSTNet: A Multilevel Spectral\u2013Spatial Transformer Network for Hyperspectral Image Classification","display_name":"MSTNet: A Multilevel Spectral\u2013Spatial Transformer Network for Hyperspectral Image Classification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285303509","doi":"https://doi.org/10.1109/tgrs.2022.3186400"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3186400","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3186400","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":["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/A5102961552","display_name":"Zhen Xu","orcid":"https://orcid.org/0009-0004-4084-5662"},"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":"middle","author":{"id":"https://openalex.org/A5020896207","display_name":"Ke Zheng","orcid":"https://orcid.org/0000-0002-0108-0511"},"institutions":[{"id":"https://openalex.org/I196934937","display_name":"Liaocheng University","ror":"https://ror.org/03yh0n709","country_code":"CN","type":"education","lineage":["https://openalex.org/I196934937"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Zheng","raw_affiliation_strings":["College of Geography and Environment, Liaocheng University, Liaocheng, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Geography and Environment, Liaocheng University, Liaocheng, China","institution_ids":["https://openalex.org/I196934937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075013625","display_name":"Danfeng Hong","orcid":"https://orcid.org/0000-0002-3212-9584"},"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":"Danfeng Hong","raw_affiliation_strings":["Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3212-9584","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/A5102002750","display_name":"Hao Yang","orcid":"https://orcid.org/0009-0009-5287-1573"},"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 Yang","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/A5101405735","display_name":"Meiping Song","orcid":"https://orcid.org/0000-0002-4489-5470"},"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":"Meiping Song","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"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.5224,"has_fulltext":false,"cited_by_count":109,"citation_normalized_percentile":{"value":0.98771121,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"60","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":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":0.9929999709129333,"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":0.963100016117096,"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":0.7828940153121948},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7703630924224854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.651364803314209},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6301043033599854},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5997204780578613},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5647352933883667},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.49412038922309875},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.48177406191825867},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.44471266865730286},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10405465960502625}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7828940153121948},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7703630924224854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.651364803314209},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6301043033599854},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5997204780578613},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5647352933883667},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.49412038922309875},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.48177406191825867},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.44471266865730286},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10405465960502625},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3186400","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3186400","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"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/9"}],"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/G5288438364","display_name":null,"funder_award_id":"3132022249","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5800071179","display_name":"\u57fa\u4e8e\u6d4b\u5ea6\u4fdd\u6301\u548c\u4efb\u52a1\u9a71\u52a8\u7684\u975e\u76d1\u7763\u6ce2\u6bb5\u9009\u62e9\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971082","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"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"}],"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"},{"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":52,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1950365613","https://openalex.org/W1966580635","https://openalex.org/W2019143339","https://openalex.org/W2029316659","https://openalex.org/W2089372326","https://openalex.org/W2116699851","https://openalex.org/W2132525626","https://openalex.org/W2164315346","https://openalex.org/W2299721312","https://openalex.org/W2519653196","https://openalex.org/W2548791488","https://openalex.org/W2602024454","https://openalex.org/W2609880332","https://openalex.org/W2611452721","https://openalex.org/W2614256707","https://openalex.org/W2735039185","https://openalex.org/W2764276316","https://openalex.org/W2767805377","https://openalex.org/W2793941577","https://openalex.org/W2798405286","https://openalex.org/W2808098982","https://openalex.org/W2908955282","https://openalex.org/W2987619624","https://openalex.org/W3012145520","https://openalex.org/W3015615500","https://openalex.org/W3036200672","https://openalex.org/W3037458146","https://openalex.org/W3043181422","https://openalex.org/W3043719198","https://openalex.org/W3047443805","https://openalex.org/W3048631361","https://openalex.org/W3091247454","https://openalex.org/W3096609285","https://openalex.org/W3099608030","https://openalex.org/W3102692100","https://openalex.org/W3103695279","https://openalex.org/W3103753223","https://openalex.org/W3104313739","https://openalex.org/W3104795559","https://openalex.org/W3105357426","https://openalex.org/W3105636206","https://openalex.org/W3114720220","https://openalex.org/W3125860323","https://openalex.org/W3128346309","https://openalex.org/W3154593456","https://openalex.org/W3165729427","https://openalex.org/W3169569276","https://openalex.org/W3204305289","https://openalex.org/W3214821343","https://openalex.org/W4205102943","https://openalex.org/W6774901790"],"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/W2343470940"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNN)":[3],"have":[4,18],"been":[5],"widely":[6],"used":[7],"in":[8,39,131,153],"hyperspectral":[9,143],"image":[10,134],"classification":[11,74,129],"(HSIC).":[12],"Although":[13],"the":[14,31,119,128,132,147,150,156],"current":[15],"CNN-based":[16,159],"methods":[17],"achieved":[19],"good":[20],"performance,":[21],"they":[22],"still":[23],"face":[24],"a":[25,43,59,87,97,108],"series":[26],"of":[27,45,69,149],"challenges.":[28],"For":[29],"example,":[30],"receptive":[32],"field":[33],"is":[34,37,71,77,101,112],"limited,":[35],"information":[36],"lost":[38],"down-sampling":[40],"layer,":[41],"and":[42,79],"lot":[44],"computing":[46],"resources":[47],"are":[48,92,122],"consumed":[49],"for":[50,65],"deep":[51],"networks.":[52],"To":[53],"overcome":[54],"these":[55],"problems,":[56],"we":[57,85],"proposed":[58,151],"multi-level":[60,120],"spectral-spatial":[61],"transformer":[62,110],"network":[63],"(MSTNet)":[64],"HSIC.":[66],"The":[67,136],"structure":[68],"MSTNet":[70],"an":[72],"image-based":[73],"framework,":[75,84],"which":[76],"efficient":[78],"straightforward.":[80],"Based":[81],"on":[82,140],"this":[83],"designed":[86],"self-attentive":[88],"encoder.":[89],"Firstly,":[90],"HSIs":[91],"processed":[93,123],"into":[94],"sequences.":[95],"Meanwhile,":[96],"learned":[98],"positional":[99],"embedding":[100],"added":[102],"to":[103,114,126],"integrate":[104],"spatial":[105],"information.":[106],"Then,":[107],"pure":[109],"encoder":[111],"employed":[113],"learn":[115],"feature":[116],"representations.":[117],"Finally,":[118],"features":[121],"by":[124],"decoders":[125],"generate":[127],"results":[130,138],"original":[133],"size.":[135],"experimental":[137],"based":[139],"three":[141],"real":[142],"data":[144],"sets":[145],"demonstrate":[146],"efficiency":[148],"method":[152],"comparison":[154],"with":[155],"other":[157],"related":[158],"methods.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":47},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}