{"id":"https://openalex.org/W4312937836","doi":"https://doi.org/10.1109/igarss46834.2022.9883118","title":"Spectral Transformer with Dynamic Spatial Sampling and Gaussian Positional Embedding for Hyperspectral Image Classification","display_name":"Spectral Transformer with Dynamic Spatial Sampling and Gaussian Positional Embedding for Hyperspectral Image Classification","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4312937836","doi":"https://doi.org/10.1109/igarss46834.2022.9883118"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9883118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883118","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 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/A5101609903","display_name":"Jiaqi Feng","orcid":"https://orcid.org/0009-0005-4185-3856"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaqi Feng","raw_affiliation_strings":["School of Astronautics, Beihang University,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"School of Astronautics, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072050541","display_name":"Xiaoyan Luo","orcid":"https://orcid.org/0000-0002-7256-4329"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Luo","raw_affiliation_strings":["School of Astronautics, Beihang University,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"School of Astronautics, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100444236","display_name":"Sen Li","orcid":"https://orcid.org/0000-0001-9906-0481"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Li","raw_affiliation_strings":["School of Astronautics, Beihang University,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"School of Astronautics, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024164148","display_name":"Qixiong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qixiong Wang","raw_affiliation_strings":["School of Astronautics, Beihang University,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"School of Astronautics, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068122673","display_name":"Jihao Yin","orcid":"https://orcid.org/0000-0002-6773-0193"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jihao Yin","raw_affiliation_strings":["School of Astronautics, Beihang University,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"School of Astronautics, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101609903"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.9586,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.79888007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.9955999851226807,"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":0.9768000245094299,"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/pixel","display_name":"Pixel","score":0.7350000143051147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7338722348213196},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7063484787940979},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.639543890953064},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6231634616851807},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6131098866462708},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.504487156867981},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4802306294441223},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47230198979377747},{"id":"https://openalex.org/keywords/data-cube","display_name":"Data cube","score":0.46227890253067017},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.15304213762283325}],"concepts":[{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7350000143051147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7338722348213196},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7063484787940979},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.639543890953064},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6231634616851807},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6131098866462708},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.504487156867981},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4802306294441223},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47230198979377747},{"id":"https://openalex.org/C78168278","wikidata":"https://www.wikidata.org/wiki/Q5227269","display_name":"Data cube","level":2,"score":0.46227890253067017},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.15304213762283325},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9883118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883118","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 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":11,"referenced_works":["https://openalex.org/W2500751094","https://openalex.org/W2764276316","https://openalex.org/W2766528611","https://openalex.org/W2898381489","https://openalex.org/W2971432438","https://openalex.org/W3047443805","https://openalex.org/W3205965083","https://openalex.org/W3214821343","https://openalex.org/W6781337563","https://openalex.org/W6797691975","https://openalex.org/W6802298689"],"related_works":["https://openalex.org/W2071211852","https://openalex.org/W3034655717","https://openalex.org/W3211035526","https://openalex.org/W4293272463","https://openalex.org/W2972973180","https://openalex.org/W1491778359","https://openalex.org/W2775464024","https://openalex.org/W2165654082","https://openalex.org/W2909041182","https://openalex.org/W2302922184"],"abstract_inverted_index":{"Owing":[0],"to":[1,12,41,49,129],"the":[2,17,27,35,38,42,74,117,123,126,130,139,151],"global":[3],"information":[4,101],"extraction":[5],"ability,":[6],"transformers":[7,53],"have":[8,21,58],"been":[9],"tentatively":[10],"applied":[11],"hyperspectral":[13],"image(HSI)":[14],"classification.":[15,97],"However,":[16],"existing":[18],"transformer-based":[19],"methods":[20],"not":[22],"made":[23],"full":[24],"use":[25],"of":[26,30,37,44,52,76,125,132,141,153,159],"flexible":[28],"characteristics":[29],"spatial":[31,66,77],"sampling":[32,67],"nor":[33],"considered":[34],"importance":[36,124],"central":[39,127],"pixel":[40,89,128],"classification":[43,131],"HSI":[45,55],"cubes.":[46],"In":[47],"order":[48],"enhance":[50],"adaptability":[51],"for":[54,96],"classification,":[56],"we":[57],"proposed":[59,155],"a":[60],"novel":[61],"spectral":[62,103,110],"transformer":[63],"with":[64],"dynamic":[65],"and":[68,115],"gaussian":[69],"positional":[70],"embedding.":[71],"To":[72,98,121],"improve":[73],"effectiveness":[75],"neighborhood":[78],"information,":[79],"Spatial":[80],"Sample":[81],"Selection(3S)":[82],"mechanism":[83],"generates":[84],"image":[85,92,133],"cube":[86,93],"from":[87],"super":[88],"region,":[90],"making":[91],"more":[94],"pure":[95],"extract":[99],"long-range":[100],"in":[102],"dimension,":[104],"Spectral":[105],"Feature":[106],"Extraction(SFE)":[107],"network":[108],"splits":[109],"bands":[111],"into":[112],"several":[113],"slices":[114],"calculates":[116],"attention":[118],"between":[119],"them.":[120],"stress":[122],"cube,":[134],"Gaussian":[135],"Positional":[136],"Embedding(GPE)":[137],"reduces":[138],"weight":[140],"surrounding":[142],"pixels":[143],"during":[144],"feature":[145],"embedding":[146],"stage.":[147],"Experimental":[148],"results":[149],"demonstrate":[150],"performance":[152],"our":[154],"method.":[156],"The":[157],"code":[158],"this":[160],"work":[161],"is":[162],"available":[163],"at":[164],"https://github.com/fengjiaqi927/HSI_transformer.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}