{"id":"https://openalex.org/W4416010746","doi":"https://doi.org/10.1109/tnnls.2025.3626142","title":"Lightweight Dual-Kernel Information Aggregation Network for Efficient Image Super-Resolution","display_name":"Lightweight Dual-Kernel Information Aggregation Network for Efficient Image Super-Resolution","publication_year":2025,"publication_date":"2025-11-07","ids":{"openalex":"https://openalex.org/W4416010746","doi":"https://doi.org/10.1109/tnnls.2025.3626142","pmid":"https://pubmed.ncbi.nlm.nih.gov/41201934"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3626142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3626142","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5001751578","display_name":"Yinggan Tang","orcid":"https://orcid.org/0000-0002-7440-1742"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yinggan Tang","raw_affiliation_strings":["School of Electrical Engineering and the Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Yanshan University, Qinhuangdao, Hebei, China"],"raw_orcid":"https://orcid.org/0000-0002-7440-1742","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and the Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Yanshan University, Qinhuangdao, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113006265","display_name":"Mengjie Su","orcid":null},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengjie Su","raw_affiliation_strings":["School of Electrical Engineering and the Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Yanshan University, Qinhuangdao, Hebei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and the Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Yanshan University, Qinhuangdao, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100709504","display_name":"Xuguang Zhang","orcid":"https://orcid.org/0000-0001-7763-0308"},"institutions":[{"id":"https://openalex.org/I4210141176","display_name":"Communication University of Zhejiang","ror":"https://ror.org/04t7gxr16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210141176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuguang Zhang","raw_affiliation_strings":["College of Media Engineering, Communication University of Zhejiang, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Media Engineering, Communication University of Zhejiang, Hangzhou, China","institution_ids":["https://openalex.org/I4210141176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5001751578"],"corresponding_institution_ids":["https://openalex.org/I39333907"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.316622,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"37","issue":"4","first_page":"1864","last_page":"1875"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9714000225067139,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9714000225067139,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.007899999618530273,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.006599999964237213,"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/convolution","display_name":"Convolution (computer science)","score":0.6998000144958496},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6974999904632568},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6176000237464905},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.5774999856948853},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.46720001101493835},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4514000117778778},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.41769999265670776},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.39259999990463257}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7921000123023987},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6998000144958496},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6974999904632568},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6176000237464905},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.5774999856948853},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.46720001101493835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4648999869823456},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4514000117778778},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.41769999265670776},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4147999882698059},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.39259999990463257},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36500000953674316},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.352400004863739},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33730000257492065},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C27602214","wikidata":"https://www.wikidata.org/wiki/Q1868547","display_name":"Locality of reference","level":3,"score":0.3012999892234802},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28119999170303345},{"id":"https://openalex.org/C2988416141","wikidata":"https://www.wikidata.org/wiki/Q6031139","display_name":"Information loss","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25859999656677246}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3626142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3626142","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:41201934","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41201934","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Efficient":[0],"single-image":[1],"super-resolution":[2,8],"(ESISR)":[3],"primarily":[4],"aims":[5],"to":[6,48,99,141,164,204],"enhance":[7],"(SR)":[9],"performance":[10,192,199,209],"while":[11,110,214],"keeping":[12],"model":[13,112,198],"complexity":[14],"low,":[15],"making":[16],"it":[17],"more":[18,144],"suitable":[19],"for":[20,147],"deployment":[21],"on":[22,143],"edge":[23],"devices.":[24],"However,":[25],"the":[26,36,77,159,170,188,220],"limited":[27],"receptive":[28,108],"field":[29,109],"caused":[30],"by":[31],"conventional":[32],"convolution's":[33],"locality":[34],"restricts":[35],"backbone":[37],"networks":[38],"and":[39,57,96,125,168,174,183,200],"attention":[40,138],"modules":[41],"from":[42],"effectively":[43],"capturing":[44],"nonlocal":[45],"features,":[46],"leading":[47],"suboptimal":[49],"SR":[50,148],"performance.":[51],"Additionally,":[52,132],"insufficient":[53],"interaction":[54,171],"between":[55,172,197],"high-":[56,173],"low-frequency":[58,175],"feature":[59,64,155,179],"information":[60,80,160],"results":[61],"in":[62,105],"incomplete":[63],"representation.":[65,180],"To":[66],"overcome":[67],"these":[68],"limitations,":[69],"we":[70,85,117,133,151],"propose":[71,134],"a":[72,87,120,126,135],"novel":[73],"ESISR":[74],"network":[75,82],"called":[76],"lightweight":[78,136],"dual-kernel":[79,88,121,127,137],"aggregation":[81,161],"(LDIAN).":[83],"First,":[84],"design":[86,152],"convolution":[89,95,98,123],"(DKC)":[90],"that":[91,187],"combines":[92],"depth-wise":[93],"1-D":[94],"dilated":[97],"efficiently":[100],"extract":[101],"richer":[102],"image":[103],"features":[104,146,167],"an":[106,153,194],"expanded":[107],"minimizing":[111],"complexity.":[113,201],"Building":[114],"upon":[115],"DKC,":[116],"further":[118],"develop":[119],"enhanced":[122,128],"(DEConv)":[124],"distillation":[129],"block":[130,162],"(DEDB).":[131],"(DKA)":[139],"mechanism":[140],"focus":[142],"representative":[145],"reconstruction.":[149],"Second,":[150],"innovative":[154],"fusion":[156],"structure":[157],"named":[158],"(IAB)":[163],"integrate":[165],"spatial":[166],"strengthen":[169],"information,":[176],"thereby":[177],"improving":[178],"Extensive":[181],"quantitative":[182],"qualitative":[184],"experiments":[185],"demonstrate":[186],"LDIAN":[189],"achieves":[190],"state-of-the-art":[191],"with":[193],"optimal":[195],"balance":[196],"Notably,":[202],"compared":[203],"SRFormer-light,":[205],"LDIAN-L":[206],"delivers":[207],"superior":[208],"across":[210],"five":[211],"standard":[212],"datasets":[213],"requiring":[215],"only":[216],"about":[217],"50%":[218],"of":[219],"model's":[221],"FLOPs.":[222]},"counts_by_year":[],"updated_date":"2026-04-07T06:01:17.266235","created_date":"2025-11-07T00:00:00"}