{"id":"https://openalex.org/W4416323884","doi":"https://doi.org/10.1109/tgrs.2025.3634114","title":"SAGT: Structure-Adaptive Graph Transformer for Hyperspectral Image Classification","display_name":"SAGT: Structure-Adaptive Graph Transformer for Hyperspectral Image Classification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416323884","doi":"https://doi.org/10.1109/tgrs.2025.3634114"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3634114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3634114","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/A5037478762","display_name":"Shuyu Zhang","orcid":"https://orcid.org/0000-0003-2038-0349"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuyu Zhang","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2038-0349","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012282514","display_name":"Shuguo Jiang","orcid":"https://orcid.org/0009-0001-9850-1043"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuguo Jiang","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0009-0001-9850-1043","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053166122","display_name":"Wenlong Yin","orcid":"https://orcid.org/0000-0003-2660-0891"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenlong Yin","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101598070","display_name":"Weixi Wang","orcid":"https://orcid.org/0000-0002-9941-7556"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixi Wang","raw_affiliation_strings":["College of Architecture and Urban Planning, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-9941-7556","affiliations":[{"raw_affiliation_string":"College of Architecture and Urban Planning, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038002446","display_name":"Meng Xu","orcid":"https://orcid.org/0000-0002-4056-7787"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Xu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-4056-7787","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051616840","display_name":"Jiasong Zhu","orcid":"https://orcid.org/0000-0001-6177-3363"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiasong Zhu","raw_affiliation_strings":["Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the Ministry of Natural Resources, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-6177-3363","affiliations":[{"raw_affiliation_string":"Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the Ministry of Natural Resources, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I211433327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035753061","display_name":"Sen Jia","orcid":"https://orcid.org/0000-0001-9742-5037"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Jia","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9742-5037","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5037478762"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45211022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9611999988555908,"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":0.9611999988555908,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.00570000009611249,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.003599999938160181,"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":0.7767999768257141},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5669999718666077},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.5534999966621399},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5418999791145325},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4862000048160553},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.483599990606308},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.3725000023841858},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3686000108718872}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7767999768257141},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.675599992275238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5698000192642212},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5669999718666077},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5534999966621399},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5418999791145325},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4862000048160553},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.483599990606308},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.3725000023841858},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3686000108718872},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3626999855041504},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.32899999618530273},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.3172999918460846},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.28439998626708984},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.2612999975681305},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3634114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3634114","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":[],"awards":[{"id":"https://openalex.org/G2998592594","display_name":null,"funder_award_id":"JCYJ20220818100206015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3433068557","display_name":null,"funder_award_id":"62271327","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3906685277","display_name":null,"funder_award_id":"62201354","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7815142065","display_name":null,"funder_award_id":"RCJC20221008092731042","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8337359579","display_name":null,"funder_award_id":"JCYJ20240813142308012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8952752513","display_name":null,"funder_award_id":"KCXFZ20240903093100001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8996696919","display_name":null,"funder_award_id":"KQTD20200909113951005","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W2057522815","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2164769329","https://openalex.org/W2194775991","https://openalex.org/W2519653196","https://openalex.org/W2531409750","https://openalex.org/W2611452721","https://openalex.org/W2614256707","https://openalex.org/W2614326984","https://openalex.org/W2768975974","https://openalex.org/W2777427437","https://openalex.org/W2789643644","https://openalex.org/W2888715336","https://openalex.org/W2892621946","https://openalex.org/W2940678725","https://openalex.org/W2963446712","https://openalex.org/W2964015378","https://openalex.org/W2964321699","https://openalex.org/W2971432438","https://openalex.org/W2991494819","https://openalex.org/W2999446243","https://openalex.org/W3028306149","https://openalex.org/W3040575072","https://openalex.org/W3047443805","https://openalex.org/W3083068801","https://openalex.org/W3111727634","https://openalex.org/W3128776197","https://openalex.org/W3138516171","https://openalex.org/W3151130473","https://openalex.org/W3200799048","https://openalex.org/W3214821343","https://openalex.org/W4210541032","https://openalex.org/W4210794570","https://openalex.org/W4220853886","https://openalex.org/W4282934494","https://openalex.org/W4283260867","https://openalex.org/W4285127355","https://openalex.org/W4285214186","https://openalex.org/W4321484009","https://openalex.org/W4327808525","https://openalex.org/W4367663440","https://openalex.org/W4385154014","https://openalex.org/W4385245566","https://openalex.org/W4386918729","https://openalex.org/W4388974348","https://openalex.org/W4391953355","https://openalex.org/W4399880035","https://openalex.org/W4402239514","https://openalex.org/W4404294159","https://openalex.org/W4406611003","https://openalex.org/W4412081524"],"related_works":[],"abstract_inverted_index":{"Hyperspectral":[0],"images":[1],"(HSIs)":[2],"are":[3,180],"vital":[4],"for":[5,108,125,239],"scene":[6],"analysis,":[7],"as":[8,93],"they":[9],"capture":[10],"detailed":[11],"spatial":[12,32,63,110,149],"and":[13,31,65,74,103,112,155,166,177,185,224],"spectral":[14,29,67,113,123,127,164],"information":[15,68,124],"to":[16,69,85,137,189,206],"characterize":[17],"surface":[18],"materials.":[19],"However,":[20],"accurate":[21],"HSI":[22,72],"classification":[23],"is":[24,83,135,221],"challenged":[25],"by":[26,142],"significant":[27],"intra-class":[28],"variability":[30,165],"complexity.":[33],"To":[34,230],"address":[35],"this,":[36],"we":[37,233],"leverage":[38],"the":[39,44,90,109,119,153,236],"fact":[40],"that":[41,59,219],"pixels":[42],"of":[43,115,121,174],"same":[45],"class":[46],"typically":[47],"form":[48],"irregular":[49,62],"local":[50],"regions.":[51],"We":[52],"propose":[53],"a":[54,78,94,130],"structure-adaptive":[55,131],"graph":[56,87,140,187],"transformer":[57],"(SAGT)":[58],"dynamically":[60,138],"captures":[61],"topologies":[64],"homogeneous":[66,122],"achieve":[70],"adaptive":[71],"representation":[73],"precise":[75],"classification.":[76],"Specifically,":[77],"structure-aware":[79],"self-attention":[80,91],"(SASA)":[81],"module":[82,134],"developed":[84],"embed":[86],"structures":[88,111,141],"into":[89],"mechanism":[92],"robust":[95,209],"positional":[96],"indicator,":[97],"which":[98,182],"can":[99],"be":[100],"extended":[101],"easily":[102],"effectively.":[104],"SASA":[105,154],"comprehensively":[106],"accounts":[107],"autocorrelation":[114],"ground":[116],"objects,":[117],"facilitating":[118],"aggregation":[120],"noise-robust":[126],"representations.":[128],"Additionally,":[129],"pooling":[132],"(SAP)":[133],"designed":[136],"adjust":[139],"discarding":[143],"irrelevant":[144],"edges,":[145],"thus":[146],"better":[147],"indicating":[148],"relationships.":[150],"By":[151],"coupling":[152],"SAP":[156],"modules,":[157],"our":[158],"proposed":[159],"SAGT":[160,220,240],"model":[161],"significantly":[162],"alleviates":[163],"tolerates":[167],"prior":[168],"noise.":[169],"Furthermore,":[170],"data":[171],"augmentation":[172],"techniques":[173],"random":[175,178],"discard":[176],"offset":[179],"built,":[181],"randomly":[183],"drop":[184],"shift":[186],"nodes":[188],"generate":[190],"more":[191,208,222],"diverse":[192],"samples":[193],"during":[194],"preprocessing.":[195],"In":[196],"postprocessing,":[197],"multiview":[198],"decision-making":[199],"integrates":[200],"results":[201,212],"from":[202],"multiple":[203],"contextual":[204],"views":[205],"provide":[207],"predictions.":[210],"Experimental":[211],"on":[213],"three":[214],"benchmark":[215],"datasets":[216],"consistently":[217],"demonstrate":[218],"effective":[223],"reliable":[225],"than":[226],"other":[227],"state-of-the-art":[228],"methods.":[229],"facilitate":[231],"reproduction,":[232],"will":[234],"release":[235],"source":[237],"code":[238],"at":[241],"https://github.com/ShuGuoJ/SAGT.git.":[242]},"counts_by_year":[],"updated_date":"2025-12-05T23:21:25.405358","created_date":"2025-11-18T00:00:00"}