{"id":"https://openalex.org/W2604459465","doi":"https://doi.org/10.1109/access.2018.2855127","title":"GUN: Gradual Upsampling Network for Single Image Super-Resolution","display_name":"GUN: Gradual Upsampling Network for Single Image Super-Resolution","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2604459465","doi":"https://doi.org/10.1109/access.2018.2855127","mag":"2604459465"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2855127","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2855127","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2855127","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021991838","display_name":"Yang Zhao","orcid":"https://orcid.org/0000-0002-4032-8049"},"institutions":[{"id":"https://openalex.org/I4210164386","display_name":"Hebei Science and Technology Department","ror":"https://ror.org/05k812a28","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210164386"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Zhao","raw_affiliation_strings":["Science and Technology on Communication Networks Laboratory, Shijiazhuang, China"],"affiliations":[{"raw_affiliation_string":"Science and Technology on Communication Networks Laboratory, Shijiazhuang, China","institution_ids":["https://openalex.org/I4210164386"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368565","display_name":"Guoqing Li","orcid":"https://orcid.org/0000-0002-2836-6413"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guoqing Li","raw_affiliation_strings":["Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100694546","display_name":"Wenjun Xie","orcid":"https://orcid.org/0000-0003-1292-3868"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenjun Xie","raw_affiliation_strings":["Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395308","display_name":"Wei Jia","orcid":"https://orcid.org/0000-0001-5628-6237"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Jia","raw_affiliation_strings":["Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089485721","display_name":"Hai Min","orcid":"https://orcid.org/0000-0002-6451-652X"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai Min","raw_affiliation_strings":["School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100616339","display_name":"Xiaoping Liu","orcid":"https://orcid.org/0000-0002-0760-6262"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoping Liu","raw_affiliation_strings":["Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5021991838"],"corresponding_institution_ids":["https://openalex.org/I4210164386"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.3872,"has_fulltext":false,"cited_by_count":59,"citation_normalized_percentile":{"value":0.96020382,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"39363","last_page":"39374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9990000128746033,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9965999722480774,"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/upsampling","display_name":"Upsampling","score":0.9827139377593994},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8066163063049316},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7334397435188293},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.646239161491394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5930740237236023},{"id":"https://openalex.org/keywords/magnification","display_name":"Magnification","score":0.5841328501701355},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.5163313150405884},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.49676400423049927},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4844777584075928},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46842870116233826},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4102208912372589},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3881060779094696},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.346275269985199},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.061446160078048706}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9827139377593994},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8066163063049316},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7334397435188293},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.646239161491394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5930740237236023},{"id":"https://openalex.org/C4144372","wikidata":"https://www.wikidata.org/wiki/Q675287","display_name":"Magnification","level":2,"score":0.5841328501701355},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.5163313150405884},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.49676400423049927},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4844777584075928},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46842870116233826},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4102208912372589},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3881060779094696},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.346275269985199},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.061446160078048706},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2855127","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2855127","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2a727c1c6a144ad08ccbe17967c7f355","is_oa":true,"landing_page_url":"https://doaj.org/article/2a727c1c6a144ad08ccbe17967c7f355","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 39363-39374 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2855127","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2855127","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2399319115","display_name":null,"funder_award_id":"61702154","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3473720878","display_name":null,"funder_award_id":"PA2018GDQT0014","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5060402580","display_name":null,"funder_award_id":"61402018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7432423553","display_name":null,"funder_award_id":"JZ2017HGTB0189","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G970020396","display_name":null,"funder_award_id":"JZ2018HGBH0280","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W7682646","https://openalex.org/W135113724","https://openalex.org/W648143168","https://openalex.org/W935139217","https://openalex.org/W1560514726","https://openalex.org/W1686810756","https://openalex.org/W1791560514","https://openalex.org/W1885185971","https://openalex.org/W1893585201","https://openalex.org/W1919542679","https://openalex.org/W1950594372","https://openalex.org/W1963882359","https://openalex.org/W1967212196","https://openalex.org/W1976416062","https://openalex.org/W1978749115","https://openalex.org/W1985436611","https://openalex.org/W1990566152","https://openalex.org/W1992408872","https://openalex.org/W1995228944","https://openalex.org/W1995258445","https://openalex.org/W2012340427","https://openalex.org/W2015374556","https://openalex.org/W2016980974","https://openalex.org/W2029684123","https://openalex.org/W2030428805","https://openalex.org/W2032916342","https://openalex.org/W2039539938","https://openalex.org/W2047920195","https://openalex.org/W2057065563","https://openalex.org/W2057817757","https://openalex.org/W2061398022","https://openalex.org/W2081385919","https://openalex.org/W2087401054","https://openalex.org/W2113524221","https://openalex.org/W2117865218","https://openalex.org/W2118963448","https://openalex.org/W2121058967","https://openalex.org/W2123613719","https://openalex.org/W2131349449","https://openalex.org/W2133665775","https://openalex.org/W2142884912","https://openalex.org/W2144870453","https://openalex.org/W2146782367","https://openalex.org/W2148312679","https://openalex.org/W2149760002","https://openalex.org/W2150081556","https://openalex.org/W2157494358","https://openalex.org/W2163480287","https://openalex.org/W2163935418","https://openalex.org/W2164551808","https://openalex.org/W2167191464","https://openalex.org/W2172128189","https://openalex.org/W2184360182","https://openalex.org/W2200594420","https://openalex.org/W2202656999","https://openalex.org/W2214802144","https://openalex.org/W2242218935","https://openalex.org/W2250093075","https://openalex.org/W2344073393","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2520322935","https://openalex.org/W2534320940","https://openalex.org/W2592533706","https://openalex.org/W2607041014","https://openalex.org/W2739757502","https://openalex.org/W2780995059","https://openalex.org/W2951523806","https://openalex.org/W2952849295","https://openalex.org/W2963037581","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W3104720471","https://openalex.org/W3137074406","https://openalex.org/W6600294690","https://openalex.org/W6605397647","https://openalex.org/W6621378261","https://openalex.org/W6624640001","https://openalex.org/W6638194035","https://openalex.org/W6642098062","https://openalex.org/W6683680428","https://openalex.org/W6686186229","https://openalex.org/W6691590550","https://openalex.org/W6704510241"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W4256609757","https://openalex.org/W2152595177","https://openalex.org/W2041117173","https://openalex.org/W2607795551","https://openalex.org/W2362774332","https://openalex.org/W2964954556","https://openalex.org/W3004135429","https://openalex.org/W201295475","https://openalex.org/W3121005460"],"abstract_inverted_index":{"In":[0,127],"this":[1],"paper,":[2],"an":[3,77,86,132],"efficient":[4],"super-resolution":[5],"(SR)":[6],"method":[7],"based":[8],"on":[9,170],"deep":[10],"convolutional":[11,83],"neural":[12],"network":[13,20,97,134],"(CNN)":[14],"is":[15,122,162],"proposed,":[16],"namely":[17],"gradual":[18,64,93,119],"upsampling":[19,81,107],"(GUN).":[21],"Recent":[22],"CNN-based":[23],"SR":[24,102],"methods":[25],"often":[26],"preliminarily":[27],"magnify":[28],"the":[29,40,46,52,56,92,95,100,125,128,144,175,178],"low-resolution":[30],"(LR)":[31],"input":[32,36,48,78],"to":[33,104,164],"high-resolution":[34],"(HR)":[35],"and":[37,49,82,85,142,158,161],"then":[38,50],"reconstruct":[39,45],"HR":[41,53],"input,":[42],"or":[43],"directly":[44],"LR":[47],"recover":[51,156],"result":[54],"at":[55],"last":[57],"layer.":[58,88],"The":[59,73,153,167],"proposed":[60,96,129,179],"GUN":[61,74,154],"utilizes":[62],"a":[63,118],"process":[65],"instead":[66],"of":[67,76,91,177],"these":[68],"two":[69],"commonly":[70],"used":[71],"frameworks.":[72],"consists":[75],"layer,":[79],"multiple":[80],"layers,":[84],"output":[87],"By":[89],"means":[90],"process,":[94,131],"can":[98,135,155],"simplify":[99],"direct":[101],"problem":[103],"multistep":[105],"easier":[106],"tasks":[108],"with":[109,139,149],"very":[110],"small":[111],"magnification":[112],"factor":[113],"in":[114],"each":[115],"step.":[116],"Furthermore,":[117],"training":[120,130],"strategy":[121],"presented":[123],"for":[124],"GUN.":[126],"initial":[133],"be":[136,165],"easily":[137],"trained":[138],"edgelike":[140],"samples,":[141],"then,":[143],"weights":[145],"are":[146],"gradually":[147],"tuned":[148],"more":[150],"complex":[151],"samples.":[152],"fine":[157],"vivid":[159],"results":[160,169],"easy":[163],"trained.":[166],"experimental":[168],"several":[171],"image":[172],"sets":[173],"demonstrate":[174],"effectiveness":[176],"network.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":14},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}