{"id":"https://openalex.org/W7130663755","doi":"https://doi.org/10.3390/computers15020133","title":"Image Deraining Using Transformer Network with Sparse Non-Local Self-Attention","display_name":"Image Deraining Using Transformer Network with Sparse Non-Local Self-Attention","publication_year":2026,"publication_date":"2026-02-20","ids":{"openalex":"https://openalex.org/W7130663755","doi":"https://doi.org/10.3390/computers15020133"},"language":"en","primary_location":{"id":"doi:10.3390/computers15020133","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers15020133","pdf_url":"https://www.mdpi.com/2073-431X/15/2/133/pdf?version=1771578247","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-431X/15/2/133/pdf?version=1771578247","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078956674","display_name":"Xueying Zhao","orcid":"https://orcid.org/0000-0003-4184-7040"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueying Zhao","raw_affiliation_strings":["School of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110136, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110136, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yufeng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yufeng Li","raw_affiliation_strings":["School of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110136, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110136, China","institution_ids":["https://openalex.org/I125904092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125904092"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3030111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":"2","first_page":"133","last_page":"133"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.8248000144958496,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.8248000144958496,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.04690000042319298,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.0364999994635582,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6062999963760376},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5669000148773193},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.5529999732971191},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49950000643730164},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4546999931335449},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45179998874664307},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.40529999136924744},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.3668000102043152}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6844000220298767},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6062999963760376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5934000015258789},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5669000148773193},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.5529999732971191},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49950000643730164},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4546999931335449},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45179998874664307},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.3668000102043152},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3402999937534332},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.3377000093460083},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.311599999666214},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27900001406669617},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26080000400543213}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/computers15020133","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers15020133","pdf_url":"https://www.mdpi.com/2073-431X/15/2/133/pdf?version=1771578247","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:620d048245724954b7e7291ab2d58bed","is_oa":false,"landing_page_url":"https://doaj.org/article/620d048245724954b7e7291ab2d58bed","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computers, Vol 15, Iss 2, p 133 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/computers15020133","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers15020133","pdf_url":"https://www.mdpi.com/2073-431X/15/2/133/pdf?version=1771578247","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4176030158996582}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7130663755.pdf","grobid_xml":"https://content.openalex.org/works/W7130663755.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W2121396509","https://openalex.org/W2133665775","https://openalex.org/W2466666260","https://openalex.org/W2509784253","https://openalex.org/W2559264300","https://openalex.org/W2592939477","https://openalex.org/W2740982616","https://openalex.org/W2884068670","https://openalex.org/W2912435603","https://openalex.org/W2963017889","https://openalex.org/W2963878020","https://openalex.org/W2964212750","https://openalex.org/W2980047233","https://openalex.org/W3034885317","https://openalex.org/W3035326127","https://openalex.org/W3170697543","https://openalex.org/W4225672218","https://openalex.org/W4283023197","https://openalex.org/W4312389762","https://openalex.org/W4312399981","https://openalex.org/W4312452088","https://openalex.org/W4312784114","https://openalex.org/W4312812783","https://openalex.org/W4312908055","https://openalex.org/W4313022653","https://openalex.org/W4385801723","https://openalex.org/W4387373207","https://openalex.org/W4393150030","https://openalex.org/W4393156585","https://openalex.org/W4402082889","https://openalex.org/W4402727831","https://openalex.org/W4404170626","https://openalex.org/W4404295307","https://openalex.org/W4404439861","https://openalex.org/W4405995258","https://openalex.org/W4406140371","https://openalex.org/W4409365790","https://openalex.org/W4412019690","https://openalex.org/W4412928865","https://openalex.org/W4413144249","https://openalex.org/W4413778024","https://openalex.org/W4414197408"],"related_works":[],"abstract_inverted_index":{"In":[0,36],"recent":[1],"years,":[2],"Transformer":[3,74],"architectures":[4],"have":[5,124,144],"excelled":[6],"at":[7],"modeling":[8],"non-local":[9,78,88],"information.":[10],"This":[11,33],"makes":[12],"them":[13],"suitable":[14],"for":[15,135],"image":[16,72],"deraining.":[17],"However,":[18],"existing":[19],"methods":[20],"use":[21],"dense":[22],"self-attention.":[23,79],"They":[24],"compute":[25],"all":[26],"similarities":[27,117],"between":[28],"query":[29],"and":[30,50,98],"key":[31],"tokens.":[32],"is":[34],"inefficient.":[35],"practice,":[37],"this":[38,66,68],"approach":[39],"can":[40],"lead":[41],"to":[42,130],"the":[43,46,60,83,104,114,146],"neglect":[44],"of":[45,56,82,86,148],"most":[47,115],"relevant":[48],"information":[49],"result":[51],"in":[52],"a":[53,94,99,126],"blurring":[54],"effect":[55],"irrelevant":[57],"representations":[58,134],"during":[59],"feature":[61,89],"aggregation":[62],"process.":[63],"To":[64],"address":[65],"issue,":[67],"paper":[69],"proposes":[70],"an":[71],"deraining":[73],"based":[75,118],"on":[76,119,141],"sparse":[77,95,100,110,127],"The":[80],"core":[81],"network":[84,97,102,129],"consists":[85],"multiple":[87],"extraction":[90],"modules,":[91],"primarily":[92],"comprising":[93],"self-attention":[96],"feedforward":[101,128],"along":[103],"channel":[105],"dimension.":[106],"Specifically,":[107],"we":[108,123],"implement":[109],"attention":[111],"by":[112],"selecting":[113],"useful":[116],"Top-k":[120],"approximations.":[121],"Furthermore,":[122],"developed":[125],"achieve":[131],"more":[132],"accurate":[133],"high-quality":[136],"preservation":[137],"results.":[138],"Extensive":[139],"experiments":[140],"benchmark":[142],"datasets":[143],"demonstrated":[145],"effectiveness":[147],"our":[149],"proposed":[150],"method.":[151]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-02-20T00:00:00"}
