{"id":"https://openalex.org/W4312942970","doi":"https://doi.org/10.1109/icpr56361.2022.9956396","title":"Hierarchical Unified Spectral-Spatial Aggregated Transformer for Hyperspectral Image Classification","display_name":"Hierarchical Unified Spectral-Spatial Aggregated Transformer for Hyperspectral Image Classification","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312942970","doi":"https://doi.org/10.1109/icpr56361.2022.9956396"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956396","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5029724037","display_name":"Weilian Zhou","orcid":"https://orcid.org/0000-0002-2071-1489"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Weilian Zhou","raw_affiliation_strings":["Waseda University,Graduate School of Information, Production and Systems,Kitakyushu,Japan","Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Graduate School of Information, Production and Systems,Kitakyushu,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066452160","display_name":"Sei\u2010ichiro Kamata","orcid":"https://orcid.org/0000-0002-1496-2417"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sei-Ichiro Kamata","raw_affiliation_strings":["Waseda University,Graduate School of Information, Production and Systems,Kitakyushu,Japan","Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Graduate School of Information, Production and Systems,Kitakyushu,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014321050","display_name":"Zhengbo Luo","orcid":"https://orcid.org/0000-0003-1662-6166"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhengbo Luo","raw_affiliation_strings":["Waseda University,Graduate School of Information, Production and Systems,Kitakyushu,Japan","Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Graduate School of Information, Production and Systems,Kitakyushu,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015958624","display_name":"Xiaoyue Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiaoyue Chen","raw_affiliation_strings":["Waseda University,Graduate School of Information, Production and Systems,Kitakyushu,Japan","Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Graduate School of Information, Production and Systems,Kitakyushu,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3041","last_page":"3047"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9965000152587891,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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":0.8420618176460266},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.663874089717865},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6575337052345276},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6315585374832153},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5721256732940674},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5382900238037109},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.4144720137119293},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1805649697780609},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07543724775314331}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8420618176460266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.663874089717865},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6575337052345276},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6315585374832153},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5721256732940674},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5382900238037109},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.4144720137119293},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1805649697780609},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07543724775314331},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956396","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G712057848","display_name":"Image Recognition and Retrieval Using Sparse Hypergraph Networks and Application to Medication Dispensing Error Prevention","funder_award_id":"21K11946","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2029316659","https://openalex.org/W2194775991","https://openalex.org/W2500751094","https://openalex.org/W2565639579","https://openalex.org/W2609880332","https://openalex.org/W2765904812","https://openalex.org/W2767074788","https://openalex.org/W2767805377","https://openalex.org/W2782517596","https://openalex.org/W2793941577","https://openalex.org/W2800371750","https://openalex.org/W2803552875","https://openalex.org/W2884585870","https://openalex.org/W2888715336","https://openalex.org/W2942454403","https://openalex.org/W2963446712","https://openalex.org/W2971432438","https://openalex.org/W2989871747","https://openalex.org/W3006984222","https://openalex.org/W3040978759","https://openalex.org/W3094502228","https://openalex.org/W3107358227","https://openalex.org/W3121523901","https://openalex.org/W3128776197","https://openalex.org/W3131500599","https://openalex.org/W3134486524","https://openalex.org/W3138516171","https://openalex.org/W3165607318","https://openalex.org/W3171087525","https://openalex.org/W3171853541","https://openalex.org/W3172801447","https://openalex.org/W3175515048","https://openalex.org/W3181955139","https://openalex.org/W3214821343","https://openalex.org/W4205342161","https://openalex.org/W4210794570","https://openalex.org/W4214493665","https://openalex.org/W4221159602","https://openalex.org/W4287116734","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6753412334","https://openalex.org/W6784333009","https://openalex.org/W6788138943","https://openalex.org/W6796721132","https://openalex.org/W6796931752","https://openalex.org/W6797533734","https://openalex.org/W6798160016","https://openalex.org/W6798274885","https://openalex.org/W6810041613"],"related_works":["https://openalex.org/W2375684291","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/W2354676191","https://openalex.org/W2044184146","https://openalex.org/W4313014865"],"abstract_inverted_index":{"Vision":[0],"Transformer":[1],"(ViT)":[2],"has":[3],"recently":[4],"been":[5],"introduced":[6],"into":[7],"the":[8,78,111,139,147],"computer":[9],"vision":[10,116],"(CV)":[11],"field":[12],"with":[13,118],"its":[14],"self-attention":[15,40],"mechanism":[16],"and":[17,86,131,141],"gotten":[18],"remarkable":[19],"performance.":[20],"However,":[21],"simply":[22],"applying":[23],"ViT":[24,36,50,62,73,87,104],"for":[25,72,107],"hyperspectral":[26],"image":[27],"(HSI)":[28],"classification":[29,109,152],"is":[30,37],"not":[31,64,75],"applicable":[32],"due":[33],"to":[34,99,137],"1)":[35,114],"a":[38,91,101,133,145],"spatial-only":[39,123],"model,":[41],"but":[42,55],"rich":[43],"spectral":[44,140],"information":[45],"exists":[46],"in":[47],"HSI;":[48],"2)":[49,122],"needs":[51],"sufficient":[52],"training":[53],"samples,":[54],"HSI":[56,108],"suffers":[57],"from":[58,90],"limited":[59],"samples;":[60],"3)":[61,126],"does":[63],"well":[65],"learn":[66],"local":[67],"features;":[68],"4)":[69,132],"multi-scale":[70],"features":[71],"are":[74],"considered.":[76],"Furthermore,":[77],"methods":[79],"which":[80],"combine":[81],"convolutional":[82],"neural":[83],"network":[84],"(CNN)":[85],"generally":[88],"suffer":[89],"large":[92],"computational":[93],"burden.":[94],"Hence,":[95],"this":[96],"paper":[97],"tends":[98],"design":[100],"suitable":[102],"pure":[103],"based":[105],"model":[106],"as":[110],"following":[112],"points:":[113],"spectral-only":[115],"transformer":[117],"all":[119],"tokens\u2019":[120],"aggregation;":[121],"local-global":[124,128],"transformer;":[125],"cross-scale":[127],"feature":[129],"fusion,":[130],"cooperative":[134],"loss":[135],"function":[136],"unify":[138],"spatial":[142],"features.":[143],"As":[144],"result,":[146],"proposed":[148],"idea":[149],"achieves":[150],"competitive":[151],"performance":[153],"on":[154],"three":[155],"public":[156],"datasets":[157],"than":[158],"other":[159],"state-of-the-art":[160],"methods.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
