{"id":"https://openalex.org/W4224937218","doi":"https://doi.org/10.1109/tim.2022.3191664","title":"SwinFuse: A Residual Swin Transformer Fusion Network for Infrared and Visible Images","display_name":"SwinFuse: A Residual Swin Transformer Fusion Network for Infrared and Visible Images","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4224937218","doi":"https://doi.org/10.1109/tim.2022.3191664"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3191664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3191664","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5086585682","display_name":"Zhishe Wang","orcid":"https://orcid.org/0000-0002-0763-5901"},"institutions":[{"id":"https://openalex.org/I46305995","display_name":"Taiyuan University of Science and Technology","ror":"https://ror.org/01wcbdc92","country_code":"CN","type":"education","lineage":["https://openalex.org/I46305995"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhishe Wang","raw_affiliation_strings":["School of Applied Science, Taiyuan University of Science and Technology, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0002-0763-5901","affiliations":[{"raw_affiliation_string":"School of Applied Science, Taiyuan University of Science and Technology, Taiyuan, China","institution_ids":["https://openalex.org/I46305995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029943079","display_name":"Yanlin Chen","orcid":"https://orcid.org/0000-0003-2276-5744"},"institutions":[{"id":"https://openalex.org/I46305995","display_name":"Taiyuan University of Science and Technology","ror":"https://ror.org/01wcbdc92","country_code":"CN","type":"education","lineage":["https://openalex.org/I46305995"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanlin Chen","raw_affiliation_strings":["School of Applied Science, Taiyuan University of Science and Technology, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0003-2276-5744","affiliations":[{"raw_affiliation_string":"School of Applied Science, Taiyuan University of Science and Technology, Taiyuan, China","institution_ids":["https://openalex.org/I46305995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070438805","display_name":"Wenyu Shao","orcid":"https://orcid.org/0000-0003-3934-1323"},"institutions":[{"id":"https://openalex.org/I46305995","display_name":"Taiyuan University of Science and Technology","ror":"https://ror.org/01wcbdc92","country_code":"CN","type":"education","lineage":["https://openalex.org/I46305995"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyu Shao","raw_affiliation_strings":["School of Applied Science, Taiyuan University of Science and Technology, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0003-3934-1323","affiliations":[{"raw_affiliation_string":"School of Applied Science, Taiyuan University of Science and Technology, Taiyuan, China","institution_ids":["https://openalex.org/I46305995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064149604","display_name":"Hui Li","orcid":"https://orcid.org/0000-0003-4550-7879"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Li","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"],"raw_orcid":"https://orcid.org/0000-0003-4550-7879","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030996066","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-3941-4804"},"institutions":[{"id":"https://openalex.org/I4210110718","display_name":"Nanyang Normal University","ror":"https://ror.org/01f7yer47","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110718"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["School of Mechatronic Engineering, Nanyang Normal University, Nanyang, China"],"raw_orcid":"https://orcid.org/0000-0002-3941-4804","affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Nanyang Normal University, Nanyang, China","institution_ids":["https://openalex.org/I4210110718"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":12.6202,"has_fulltext":false,"cited_by_count":160,"citation_normalized_percentile":{"value":0.99157609,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","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/T11659","display_name":"Advanced Image Fusion Techniques","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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9980000257492065,"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":0.9958000183105469,"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/residual","display_name":"Residual","score":0.7038539052009583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6736837029457092},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6473335027694702},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6324300169944763},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6257995367050171},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5895940661430359},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5527037978172302},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5418393015861511},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4787299335002899},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.43419232964515686},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2899613678455353},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13987529277801514}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7038539052009583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6736837029457092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6473335027694702},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6324300169944763},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6257995367050171},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5895940661430359},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5527037978172302},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5418393015861511},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4787299335002899},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.43419232964515686},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2899613678455353},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13987529277801514},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"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/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/tim.2022.3191664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3191664","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1580436348","https://openalex.org/W1708141795","https://openalex.org/W1756233291","https://openalex.org/W1861492603","https://openalex.org/W1964641132","https://openalex.org/W2054273865","https://openalex.org/W2142060261","https://openalex.org/W2153777140","https://openalex.org/W2221102299","https://openalex.org/W2589745805","https://openalex.org/W2798987894","https://openalex.org/W2912147220","https://openalex.org/W2961165092","https://openalex.org/W2963597983","https://openalex.org/W2963787388","https://openalex.org/W2978622574","https://openalex.org/W2998012573","https://openalex.org/W3007891240","https://openalex.org/W3011768656","https://openalex.org/W3023203534","https://openalex.org/W3030921250","https://openalex.org/W3039415429","https://openalex.org/W3043904761","https://openalex.org/W3046194589","https://openalex.org/W3083923056","https://openalex.org/W3092444386","https://openalex.org/W3102411220","https://openalex.org/W3105639468","https://openalex.org/W3108042295","https://openalex.org/W3121751387","https://openalex.org/W3129015415","https://openalex.org/W3133700567","https://openalex.org/W3138516171","https://openalex.org/W3143068962","https://openalex.org/W3158080681","https://openalex.org/W3163132162","https://openalex.org/W3181367324","https://openalex.org/W3198582484","https://openalex.org/W3207918547","https://openalex.org/W3215775659","https://openalex.org/W3216987090","https://openalex.org/W4206390057","https://openalex.org/W4206522033","https://openalex.org/W4225654135","https://openalex.org/W4226077544","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6805147364"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2788972299","https://openalex.org/W2521347458","https://openalex.org/W2498789492","https://openalex.org/W2729981612","https://openalex.org/W4233449973","https://openalex.org/W2925692864","https://openalex.org/W4391013256","https://openalex.org/W4309346246"],"abstract_inverted_index":{"The":[0,195],"existing":[1],"deep":[2,161],"learning":[3,162],"fusion":[4,43,54,77,121,185],"methods":[5,163],"mainly":[6],"concentrate":[7],"on":[8,164],"the":[9,21,29,73,94,111,130,175,180],"convolutional":[10,22,112],"neural":[11,113],"networks,":[12],"and":[13,31,40,52,58,79,103,128,136,147,160,171,174,191],"few":[14],"attempts":[15],"are":[16],"made":[17],"with":[18,110,156,187],"transformer.":[19],"Meanwhile,":[20],"operation":[23],"is":[24,98],"a":[25,50,86,99,105,118],"content-independent":[26],"interaction":[27],"between":[28],"image":[30],"convolution":[32],"kernel,":[33],"which":[34,97,140],"may":[35],"lose":[36],"some":[37],"important":[38],"contexts":[39],"further":[41],"limit":[42],"performance.":[44],"Towards":[45],"this":[46],"end,":[47],"we":[48,84,116,152],"present":[49],"simple":[51],"strong":[53,188],"baseline":[55],"for":[56,125],"infrared":[57,145],"visible":[59,149],"images,":[60],"namelyResidual":[61],"Swin":[62],"Transformer":[63],"Fusion":[64],"Network,":[65],"termed":[66],"SwinFuse.":[67],"Our":[68],"SwinFuse":[69,155,182],"includes":[70],"three":[71,165],"parts:":[72],"global":[74],"feature":[75,80,89,120],"extraction,":[76],"layer":[78],"reconstruction.":[81],"In":[82],"particular,":[83],"build":[85],"fully":[87],"attentional":[88],"encoding":[90],"backbone":[91],"to":[92],"model":[93],"long-range":[95],"dependency,":[96],"pure":[100],"transformer":[101],"network":[102],"has":[104],"stronger":[106],"representation":[107],"ability":[108,190],"compared":[109],"networks.":[114],"Moreover,":[115],"design":[117],"novel":[119],"strategy":[122],"based":[123],"onL1-norm":[124],"sequence":[126],"matrices,":[127],"measure":[129],"corresponding":[131],"activity":[132],"levels":[133],"from":[134],"row":[135],"column":[137],"vector":[138],"dimensions,":[139],"can":[141],"well":[142],"retain":[143],"competitive":[144,192],"brightness":[146],"distinct":[148],"details.":[150],"Finally,":[151],"testify":[153],"our":[154],"nine":[157],"state-of-the-art":[158],"traditional":[159],"different":[166],"datasets":[167],"through":[168],"subjective":[169],"observations":[170],"objective":[172],"comparisons,":[173],"experimental":[176],"results":[177],"manifest":[178],"that":[179],"proposed":[181],"obtains":[183],"surprising":[184],"performance":[186],"generalization":[189],"computational":[193],"efficiency.":[194],"code":[196],"will":[197],"be":[198],"available":[199],"at":[200],"https://github.com/Zhishe-Wang/SwinFuse.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":18},{"year":2025,"cited_by_count":57},{"year":2024,"cited_by_count":53},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":6}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}