{"id":"https://openalex.org/W4408355704","doi":"https://doi.org/10.1109/icassp49660.2025.10888463","title":"Efficient Global Attention and Correlation-Aware Fusion for Hyperspectral Image Classification","display_name":"Efficient Global Attention and Correlation-Aware Fusion for Hyperspectral Image Classification","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408355704","doi":"https://doi.org/10.1109/icassp49660.2025.10888463"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10888463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5077065803","display_name":"Hongkang Zhang","orcid":"https://orcid.org/0009-0007-8919-7629"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongkang Zhang","raw_affiliation_strings":["Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088293566","display_name":"Shao\u2010Lun Huang","orcid":"https://orcid.org/0000-0003-2827-4022"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shao-Lun Huang","raw_affiliation_strings":["Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038228706","display_name":"Er\u00e7an E. Kuruo\u011flu","orcid":"https://orcid.org/0000-0002-2608-8034"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ercan Engin Kuruoglu","raw_affiliation_strings":["Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.991599977016449,"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":0.991599977016449,"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":0.9796000123023987,"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":0.9404000043869019,"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":0.8563495874404907},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6819737553596497},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6573745608329773},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5872227549552917},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5415700674057007},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5071911811828613},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5036086440086365},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.45223376154899597},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42176252603530884},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.407866507768631},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18342870473861694}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8563495874404907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6819737553596497},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6573745608329773},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5872227549552917},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5415700674057007},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5071911811828613},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5036086440086365},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.45223376154899597},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42176252603530884},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.407866507768631},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18342870473861694},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10888463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2752782242","https://openalex.org/W2799390666","https://openalex.org/W2806437580","https://openalex.org/W2888119354","https://openalex.org/W2891513880","https://openalex.org/W2950185713","https://openalex.org/W2955058313","https://openalex.org/W2966358285","https://openalex.org/W2966751049","https://openalex.org/W2983491485","https://openalex.org/W3013882333","https://openalex.org/W3127148410","https://openalex.org/W3128571866","https://openalex.org/W3148263657","https://openalex.org/W3171853541","https://openalex.org/W3195257276","https://openalex.org/W3205965083","https://openalex.org/W3214821343","https://openalex.org/W4200154985","https://openalex.org/W4200507278","https://openalex.org/W4200525139","https://openalex.org/W4210794570","https://openalex.org/W4212802630","https://openalex.org/W4220853886","https://openalex.org/W4225630686","https://openalex.org/W4226271316","https://openalex.org/W4281790783","https://openalex.org/W4285124290","https://openalex.org/W4294663621","https://openalex.org/W4315473866","https://openalex.org/W4319069095","https://openalex.org/W4319336416","https://openalex.org/W4383752953","https://openalex.org/W4388543795","https://openalex.org/W4391382946","https://openalex.org/W4392903274","https://openalex.org/W4401806915","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969","https://openalex.org/W2284201331","https://openalex.org/W2095903272","https://openalex.org/W1989561795"],"abstract_inverted_index":{"Hyperspectral":[0],"imaging":[1],"offers":[2],"extensive":[3],"spectral":[4,115],"and":[5,32,59,131,153],"spatial":[6],"information.":[7],"However,":[8],"effectively":[9],"utilizing":[10],"this":[11],"data":[12,37],"for":[13,38,67,74],"accurate":[14],"classification":[15,151],"remains":[16],"a":[17,24,45,52],"challenge.":[18],"This":[19],"study":[20],"introduced":[21],"the":[22,77,80,91,98,104,107,136,141,145,155],"CASSX-Net,":[23],"novel":[25],"framework":[26,138],"designed":[27],"to":[28,56,109],"capture":[29],"both":[30],"short-":[31],"long-range":[33,75],"dependencies":[34],"in":[35,148],"HSI":[36,123,156],"land":[39,157],"cover":[40,158],"classification.":[41,159],"The":[42,117],"network":[43],"combined":[44],"dual":[46],"spectral-spatial":[47,82],"feature":[48,61,69],"extraction":[49,70],"mechanism":[50],"with":[51,71,113],"multi-head":[53],"cross-attention":[54,72],"module":[55],"leverage":[57],"local":[58],"global":[60],"interactions.":[62],"By":[63],"combining":[64],"convolutional":[65],"layers":[66],"short-range":[68],"mechanisms":[73],"dependencies,":[76],"CASSX-Net":[78],"addressed":[79],"intricate":[81],"correlations":[83],"often":[84],"missed":[85],"by":[86],"traditional":[87],"CNNs.":[88],"In":[89],"addition,":[90],"maximal":[92],"correlation":[93],"fusion":[94],"strategy":[95],"optimally":[96],"integrated":[97],"features":[99],"from":[100],"various":[101],"pathways,":[102],"improving":[103],"ability":[105],"of":[106,120,150],"model":[108],"distinguish":[110],"between":[111],"classes":[112],"similar":[114],"signatures.":[116],"rigorous":[118],"evaluation":[119],"four":[121],"benchmark":[122],"datasets,":[124],"including":[125],"Pavia":[126,128],"University,":[127],"Centre,":[129],"Salinas,":[130],"Houston":[132],"2018,":[133],"demonstrated":[134],"that":[135],"proposed":[137],"consistently":[139],"achieved":[140],"state-of-the-art":[142],"performance,":[143],"surpassing":[144],"existing":[146],"methods":[147],"terms":[149],"accuracy":[152],"advancing":[154]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}