{"id":"https://openalex.org/W2795283978","doi":"https://doi.org/10.1109/lsp.2018.2820057","title":"A Novel Multiconnected Convolutional Network for Super-Resolution","display_name":"A Novel Multiconnected Convolutional Network for Super-Resolution","publication_year":2018,"publication_date":"2018-03-27","ids":{"openalex":"https://openalex.org/W2795283978","doi":"https://doi.org/10.1109/lsp.2018.2820057","mag":"2795283978"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2018.2820057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2018.2820057","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5089900412","display_name":"Jinghui Chu","orcid":"https://orcid.org/0000-0001-7926-8824"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghui Chu","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100349826","display_name":"Jiaqi Zhang","orcid":"https://orcid.org/0009-0009-6024-5142"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Zhang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Lu","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017194710","display_name":"Xiangdong Huang","orcid":"https://orcid.org/0000-0003-1217-3809"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangdong Huang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-1217-3809","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":1.2719,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.84825201,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"25","issue":"7","first_page":"946","last_page":"950"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"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":1.0,"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":0.9979000091552734,"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":0.9977999925613403,"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":0.692376971244812},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.514118492603302},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4446509778499603},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42701539397239685},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4116179943084717},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30604279041290283},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.13714784383773804}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.692376971244812},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.514118492603302},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4446509778499603},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42701539397239685},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4116179943084717},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30604279041290283},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.13714784383773804}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2018.2820057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2018.2820057","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W1522301498","https://openalex.org/W1665214252","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1885185971","https://openalex.org/W2097117768","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2242218935","https://openalex.org/W2302255633","https://openalex.org/W2430196102","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2560533888","https://openalex.org/W2578804018","https://openalex.org/W2588196171","https://openalex.org/W2619662254","https://openalex.org/W2726304302","https://openalex.org/W2739757502","https://openalex.org/W2741137940","https://openalex.org/W2962835968","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963583038","https://openalex.org/W2963911037","https://openalex.org/W2964121744","https://openalex.org/W6631190155","https://openalex.org/W6637242042","https://openalex.org/W6637373629","https://openalex.org/W6638444622","https://openalex.org/W6638667902","https://openalex.org/W6717870063","https://openalex.org/W6732914421"],"related_works":["https://openalex.org/W2610189143","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2159424856","https://openalex.org/W4293226380","https://openalex.org/W2136831313","https://openalex.org/W2544423928","https://openalex.org/W2119916994","https://openalex.org/W2141457018","https://openalex.org/W2374784828"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"exhibit":[3],"superior":[4],"performance":[5,136],"for":[6,58],"single":[7],"image":[8],"super-resolution":[9],"(SISR)":[10],"tasks.":[11],"However,":[12],"as":[13],"the":[14,20,33,46,63,86,110,128],"network":[15,57],"grows":[16],"deeper,":[17],"features":[18,41,84,90,108],"from":[19],"earlier":[21,34],"layers":[22,35],"are":[23,36,43],"impeded":[24],"or":[25],"less":[26],"used":[27],"in":[28,138],"later":[29,116],"layers.":[30],"In":[31,48,94],"SISR,":[32],"mainly":[37],"composed":[38],"of":[39,65,88,109,140],"local":[40],"that":[42],"essential":[44],"to":[45,79,91,96,105,126],"task.":[47],"this":[49],"letter,":[50],"we":[51,119],"present":[52],"a":[53,73,100,114,121],"novel":[54],"multiconnected":[55,77,98],"convolutional":[56],"SISR":[59],"tasks":[60],"by":[61],"enhancing":[62],"combination":[64],"both":[66,137],"low-":[67],"and":[68,82,113,143],"high-level":[69,92],"features.":[70,93],"We":[71],"design":[72],"structure":[74],"built":[75],"on":[76,152],"blocks":[78],"extract":[80],"diversified":[81],"complicated":[83],"via":[85,154],"concatenation":[87],"low-level":[89],"addition":[95],"stacking":[97],"blocks,":[99],"long":[101],"skip-connection":[102],"is":[103],"implemented":[104],"further":[106],"aggregate":[107],"first":[111],"layer":[112],"specific":[115],"layer.":[117],"Furthermore,":[118],"employ":[120],"flexible":[122],"two-parameter":[123],"loss":[124],"function":[125],"optimize":[127],"training":[129],"process.":[130],"The":[131,146],"proposed":[132],"method":[133,147],"yields":[134],"state-of-the-art":[135],"terms":[139],"quantitative":[141],"metrics":[142],"visual":[144],"quality.":[145],"also":[148],"outperforms":[149],"existing":[150],"methods":[151],"datasets":[153],"unknown":[155],"degrading":[156],"operators,":[157],"indicating":[158],"an":[159],"excellent":[160],"generalization":[161],"ability.":[162]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}