{"id":"https://openalex.org/W2547407741","doi":"https://doi.org/10.1109/newcas.2016.7604756","title":"Image super-resolution with multi-channel convolutional neural networks","display_name":"Image super-resolution with multi-channel convolutional neural networks","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2547407741","doi":"https://doi.org/10.1109/newcas.2016.7604756","mag":"2547407741"},"language":"en","primary_location":{"id":"doi:10.1109/newcas.2016.7604756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/newcas.2016.7604756","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 14th IEEE International New Circuits and Systems Conference (NEWCAS)","raw_type":"proceedings-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/A5101197745","display_name":"Yu Kato","orcid":null},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yu Kato","raw_affiliation_strings":["Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002147780","display_name":"Shinya Ohtani","orcid":null},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinya Ohtani","raw_affiliation_strings":["Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089221161","display_name":"Nobutaka Kuroki","orcid":"https://orcid.org/0000-0002-8288-0747"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobutaka Kuroki","raw_affiliation_strings":["Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101737932","display_name":"Tetsuya Hirose","orcid":"https://orcid.org/0000-0003-1997-5097"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Hirose","raw_affiliation_strings":["Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070530869","display_name":"Masahiro Numa","orcid":null},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Numa","raw_affiliation_strings":["Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Kobe University 1-1 Rokkodai, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.507,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.73671998,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9958999752998352,"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":0.991100013256073,"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/bicubic-interpolation","display_name":"Bicubic interpolation","score":0.8639644384384155},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8251497149467468},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7481528520584106},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6780086755752563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6564021110534668},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6531565189361572},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6383144855499268},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6091720461845398},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5619072318077087},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4879745841026306},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4671950340270996},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4568222165107727},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.41428226232528687},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32263875007629395},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.29036226868629456},{"id":"https://openalex.org/keywords/linear-interpolation","display_name":"Linear interpolation","score":0.17137190699577332},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11424088478088379}],"concepts":[{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.8639644384384155},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8251497149467468},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7481528520584106},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6780086755752563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6564021110534668},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6531565189361572},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6383144855499268},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6091720461845398},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5619072318077087},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4879745841026306},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4671950340270996},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4568222165107727},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.41428226232528687},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32263875007629395},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29036226868629456},{"id":"https://openalex.org/C171836373","wikidata":"https://www.wikidata.org/wiki/Q2266329","display_name":"Linear interpolation","level":3,"score":0.17137190699577332},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11424088478088379}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/newcas.2016.7604756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/newcas.2016.7604756","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 14th IEEE International New Circuits and Systems Conference (NEWCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W935139217","https://openalex.org/W1885185971","https://openalex.org/W2047920195","https://openalex.org/W2118963448","https://openalex.org/W2121058967","https://openalex.org/W2133665775","https://openalex.org/W2149669120","https://openalex.org/W2149760002","https://openalex.org/W2150081556","https://openalex.org/W2161516371","https://openalex.org/W2202656999","https://openalex.org/W2344468648","https://openalex.org/W4285719527","https://openalex.org/W4377561911","https://openalex.org/W6624640001","https://openalex.org/W6639309558","https://openalex.org/W6682352507","https://openalex.org/W6683660953","https://openalex.org/W6704923951"],"related_works":["https://openalex.org/W2785996895","https://openalex.org/W2044092692","https://openalex.org/W2614621130","https://openalex.org/W2082925067","https://openalex.org/W2547665164","https://openalex.org/W3103111272","https://openalex.org/W4289655544","https://openalex.org/W3098848838","https://openalex.org/W1519931592","https://openalex.org/W2538403599"],"abstract_inverted_index":{"This":[0,46],"paper":[1],"proposes":[2],"image":[3],"super-resolution":[4],"techniques":[5],"with":[6],"multi-channel":[7],"convolutional":[8],"neural":[9],"networks":[10],"(CNN).":[11],"In":[12],"the":[13,35,60,64,78],"proposed":[14,65],"method,":[15],"output":[16],"pixels":[17],"are":[18,29,39],"classified":[19],"into":[20,41],"four":[21],"groups":[22,28],"depending":[23],"on":[24],"their":[25],"positions.":[26],"Those":[27],"generated":[30],"from":[31],"separate":[32],"channels":[33],"of":[34],"CNN.":[36],"Finally,":[37],"they":[38],"synthesized":[40],"a":[42],"2-2":[43],"magnified":[44],"image.":[45],"architecture":[47],"can":[48],"enlarge":[49],"images":[50],"directly":[51],"without":[52],"bicubic":[53],"interpolation.":[54],"Experimental":[55],"results":[56],"have":[57],"shown":[58],"that":[59,76],"average":[61],"PSNR":[62],"for":[63,77],"method":[66],"achieves":[67],"36.88":[68],"dB,":[69],"which":[70],"is":[71],"0.39":[72],"dB":[73],"higher":[74],"than":[75],"conventional":[79],"SRCNN.":[80]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
