{"id":"https://openalex.org/W2963103155","doi":"https://doi.org/10.1109/access.2019.2903582","title":"End-to-End Image Super-Resolution via Deep and Shallow Convolutional Networks","display_name":"End-to-End Image Super-Resolution via Deep and Shallow Convolutional Networks","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2963103155","doi":"https://doi.org/10.1109/access.2019.2903582","mag":"2963103155"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2903582","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2903582","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08666711.pdf","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://ieeexplore.ieee.org/ielx7/6287639/8600701/08666711.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100398583","display_name":"Yifan Wang","orcid":"https://orcid.org/0000-0003-1223-136X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Wang","raw_affiliation_strings":["School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0003-1223-136X","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100318892","display_name":"Lijun Wang","orcid":"https://orcid.org/0000-0003-2538-8358"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijun Wang","raw_affiliation_strings":["School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422639","display_name":"Hongyu Wang","orcid":"https://orcid.org/0000-0002-1038-412X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Wang","raw_affiliation_strings":["School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070918242","display_name":"Peihua Li","orcid":"https://orcid.org/0000-0001-7229-3867"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peihua Li","raw_affiliation_strings":["School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.8485,"has_fulltext":true,"cited_by_count":105,"citation_normalized_percentile":{"value":0.97537146,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"31959","last_page":"31970"},"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":0.9973000288009644,"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":0.9940999746322632,"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/computer-science","display_name":"Computer science","score":0.8598933219909668},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.8574193120002747},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7175008058547974},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6908223032951355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6708136200904846},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.59580397605896},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4833680987358093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4749332070350647},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4642733931541443},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.44790056347846985},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4335898160934448},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.42258328199386597},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3151184022426605}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8598933219909668},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8574193120002747},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7175008058547974},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6908223032951355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6708136200904846},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.59580397605896},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4833680987358093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4749332070350647},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4642733931541443},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.44790056347846985},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4335898160934448},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.42258328199386597},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3151184022426605},{"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":2,"locations":[{"id":"doi:10.1109/access.2019.2903582","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2903582","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08666711.pdf","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:aa6c23743f3d487ca0f981e2a9f90975","is_oa":true,"landing_page_url":"https://doaj.org/article/aa6c23743f3d487ca0f981e2a9f90975","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":"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 7, Pp 31959-31970 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2903582","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2903582","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08666711.pdf","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":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6899999976158142}],"awards":[{"id":"https://openalex.org/G1500189215","display_name":"\u9ad8\u5149\u8c31\u4e0e\u6781\u5316SAR\u56fe\u50cf\u534f\u540c\u6df1\u5ea6\u5b66\u4e60\u5206\u7c7b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61671103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4507495399","display_name":"\u57fa\u4e8e\u4fe1\u606f\u51e0\u4f55\u548c\u6d4b\u5ea6\u5b66\u4e60\u7684\u6df7\u5408\u9ad8\u65af\u6a21\u578b\u8ddd\u79bb\u7814\u7a76\u53ca\u5728\u56fe\u50cf\u5206\u7c7b\u4e2d\u7684\u5e94\u7528","funder_award_id":"61471082","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963103155.pdf","grobid_xml":"https://content.openalex.org/works/W2963103155.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W4136762","https://openalex.org/W54257720","https://openalex.org/W935139217","https://openalex.org/W1026270304","https://openalex.org/W1599195847","https://openalex.org/W1791560514","https://openalex.org/W1806901794","https://openalex.org/W1836465849","https://openalex.org/W1885185971","https://openalex.org/W1919542679","https://openalex.org/W1950594372","https://openalex.org/W1976416062","https://openalex.org/W1992408872","https://openalex.org/W2035677848","https://openalex.org/W2047920195","https://openalex.org/W2064675550","https://openalex.org/W2088254198","https://openalex.org/W2097074225","https://openalex.org/W2097117768","https://openalex.org/W2098506229","https://openalex.org/W2117865218","https://openalex.org/W2118963448","https://openalex.org/W2121058967","https://openalex.org/W2121927366","https://openalex.org/W2133665775","https://openalex.org/W2137290314","https://openalex.org/W2149760002","https://openalex.org/W2150081556","https://openalex.org/W2155893237","https://openalex.org/W2157494358","https://openalex.org/W2162915993","https://openalex.org/W2163605009","https://openalex.org/W2163935418","https://openalex.org/W2194775991","https://openalex.org/W2196707239","https://openalex.org/W2202656999","https://openalex.org/W2214802144","https://openalex.org/W2242218935","https://openalex.org/W2295107390","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2534320940","https://openalex.org/W2592088493","https://openalex.org/W2604459465","https://openalex.org/W2607041014","https://openalex.org/W2747898905","https://openalex.org/W2950621961","https://openalex.org/W2963864522","https://openalex.org/W2964101377","https://openalex.org/W2964125708","https://openalex.org/W3104720471","https://openalex.org/W3105700508","https://openalex.org/W6624640001","https://openalex.org/W6626481562","https://openalex.org/W6638194035","https://openalex.org/W6638667902","https://openalex.org/W6683680428","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709","https://openalex.org/W4306309518","https://openalex.org/W4385574037","https://openalex.org/W4212888438"],"abstract_inverted_index":{"In":[0],"this":[1,65],"paper,":[2],"we":[3,67],"propose":[4,68],"a":[5,13,31,41,52,142],"new":[6],"image":[7,92,185],"super-resolution":[8],"(SR)":[9],"approach":[10],"based":[11],"on":[12,160],"convolutional":[14],"neural":[15],"network":[16,43,81,97,109,122,182],"(CNN),":[17],"which":[18,50],"jointly":[19,70],"learns":[20],"the":[21,87,91,95,103,107,118,136,178],"feature":[22],"extraction,":[23],"upsampling,":[24],"and":[25,57,76,150,165],"high-resolution":[26],"(HR)":[27],"reconstruction":[28],"modules,":[29],"yielding":[30],"completely":[32],"end-to-end":[33,46],"trainable":[34],"deep":[35,42,75,96,121],"CNN.":[36],"However,":[37],"directly":[38],"training":[39],"such":[40],"in":[44,141],"an":[45,72],"fashion":[47],"is":[48,110,157],"challenging,":[49],"takes":[51],"longer":[53],"time":[54],"to":[55,60,69,113,145,176,184],"converge":[56],"may":[58],"lead":[59],"sub-optimal":[61],"results.":[62],"To":[63,127],"address":[64],"issue,":[66],"train":[71],"ensemble":[73],"of":[74,90,120,133,180],"shallow":[77,80,108],"networks.":[78],"The":[79,154],"with":[82,98],"weaker":[83],"learning":[84],"capability":[85],"restores":[86],"main":[88],"structure":[89],"content,":[93],"while":[94],"stronger":[99],"representation":[100],"power":[101],"captures":[102],"high-frequency":[104,137],"details.":[105],"Since":[106],"much":[111],"easier":[112],"optimize,":[114],"it":[115],"significantly":[116],"lowers":[117],"difficulty":[119],"optimization":[123],"during":[124],"joint":[125],"training.":[126],"further":[128],"ensure":[129],"more":[130],"accurate":[131],"restoration":[132],"HR":[134],"images,":[135],"details":[138],"are":[139,174],"reconstructed":[140],"multi-scale":[143],"manner":[144],"simultaneously":[146],"incorporate":[147],"both":[148],"short-":[149],"long-range":[151],"contextual":[152],"information.":[153],"proposed":[155],"method":[156],"extensively":[158],"evaluated":[159],"widely":[161],"adopted":[162],"data":[163],"sets":[164],"compares":[166],"favorably":[167],"against":[168],"state-of-the-art":[169],"methods.":[170],"In-depth":[171],"ablation":[172],"studies":[173],"conducted":[175],"verify":[177],"contributions":[179],"different":[181],"designs":[183],"SR,":[186],"providing":[187],"additional":[188],"insights":[189],"for":[190],"future":[191],"research.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":27},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
