{"id":"https://openalex.org/W7127109578","doi":"https://doi.org/10.31449/inf.v50i5.10264","title":"Dual-Channel Convolutional Neural Network with Mask Guidance for Digital Media Image Super-Resolution","display_name":"Dual-Channel Convolutional Neural Network with Mask Guidance for Digital Media Image Super-Resolution","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7127109578","doi":"https://doi.org/10.31449/inf.v50i5.10264"},"language":null,"primary_location":{"id":"doi:10.31449/inf.v50i5.10264","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i5.10264","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/10264/6428","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.informatica.si/index.php/informatica/article/download/10264/6428","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124862769","display_name":"Qian Song","orcid":null},"institutions":[{"id":"https://openalex.org/I1305126327","display_name":"Zibo Vocational Institute","ror":"https://ror.org/04mzr3655","country_code":"CN","type":"education","lineage":["https://openalex.org/I1305126327"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qian Song","raw_affiliation_strings":["Department of Animation Arts , Zibo Vocational Institute , Zibo 255300 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Animation Arts , Zibo Vocational Institute , Zibo 255300 , China","institution_ids":["https://openalex.org/I1305126327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5124862769"],"corresponding_institution_ids":["https://openalex.org/I1305126327"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10819176,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"50","issue":"5","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9717000126838684,"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":0.9717000126838684,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.00570000009611249,"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":0.002099999925121665,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6445000171661377},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5974000096321106},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5602999925613403},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.49630001187324524},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4909999966621399},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48500001430511475},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4041000008583069},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4041000008583069},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3993000090122223}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7261000275611877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6503000259399414},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6445000171661377},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5974000096321106},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5602999925613403},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.49630001187324524},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4909999966621399},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48500001430511475},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4641000032424927},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3993000090122223},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.38839998841285706},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3578000068664551},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.3564999997615814},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.3560999929904938},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.3393999934196472},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C104317675","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Digital image processing","level":4,"score":0.2705000042915344},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2630000114440918},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.26190000772476196},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.25949999690055847}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.31449/inf.v50i5.10264","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i5.10264","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/10264/6428","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.31449/inf.v50i5.10264","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i5.10264","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/10264/6428","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5472964644432068,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7127109578.pdf","grobid_xml":"https://content.openalex.org/works/W7127109578.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,46,54,71,83,102,107,141,144,168,192,216],"issues":[3],"of":[4,106,114,121,132,138,164,218],"low":[5],"resolution":[6],"and":[7,67,79,85,88,195,207,213,229],"detail":[8],"loss":[9],"in":[10,167],"digital":[11,239],"media":[12,240],"visual":[13],"image":[14,48,91,178,241],"reconstruction,":[15],"this":[16],"paper":[17],"proposes":[18],"a":[19,25,36,74,119,136,176,209],"super-resolution":[20,100],"reconstruction":[21,77,205],"algorithm":[22,33,145,202],"based":[23],"on":[24,82],"dual-channel":[26],"mask-guided":[27],"convolutional":[28],"neural":[29],"network":[30],"(CNN).":[31],"This":[32],"innovatively":[34],"designs":[35],"parallel":[37],"guidance":[38],"channel":[39,226],"that":[40,98],"utilizes":[41],"edge":[42],"masks":[43],"generated":[44],"from":[45],"input":[47],"as":[49],"prior":[50],"knowledge":[51],"to":[52,58,158,182],"enhance":[53],"main":[55],"channel's":[56],"ability":[57],"extract":[59],"high-frequency":[60],"structural":[61,125],"features.":[62],"Through":[63],"multi-layer":[64],"feature":[65,230],"fusion":[66],"improved":[68,110,128,201,204],"Adam":[69],"optimizer,":[70],"model":[72,155],"achieves":[73,208],"balance":[75,210],"between":[76,211],"quality":[78,92,206,212],"efficiency.":[80],"Tested":[81],"CIFAR-10":[84],"ILSVRC2020":[86],"datasets,":[87],"validated":[89],"using":[90],"assessment":[93],"metrics,":[94],"it":[95],"was":[96,161,187],"found":[97],"under":[99],"tasks,":[101],"peak":[103],"signal-to-noise":[104],"ratio":[105],"research":[108],"method":[109,194],"by":[111,129],"an":[112,130],"average":[113,131,172],"about":[115,133,183,188],"1.1":[116],"dB,":[117],"with":[118,135,154],"maximum":[120,137],"37.12":[122],"dB.":[123],"The":[124,171,200],"similarity":[126],"index":[127],"2.1%,":[134],"0.9682.":[139],"At":[140],"same":[142,169],"time,":[143],"demonstrated":[146,196],"excellent":[147],"efficiency":[148,214],"advantages":[149],"while":[150],"maintaining":[151],"high":[152],"performance,":[153],"parameters":[156,219],"reduced":[157,181],"1.2M,":[159],"which":[160,186],"only":[162],"1/35":[163],"advanced":[165],"models":[166],"category.":[170],"inference":[173],"time":[174],"for":[175,238],"single":[177],"has":[179],"been":[180],"20":[184],"ms,":[185],"45%":[189],"faster":[190],"than":[191],"baseline":[193],"superior":[197],"overall":[198],"performance.":[199],"offers":[203],"when":[215],"number":[217],"is":[220],"limited.":[221],"Improving":[222],"CNN":[223],"through":[224],"dual":[225],"collaborative":[227],"design":[228],"reuse":[231],"mechanisms":[232],"can":[233],"provide":[234],"new":[235],"technological":[236],"solutions":[237],"processing.":[242]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-02-03T00:00:00"}