{"id":"https://openalex.org/W4291907811","doi":"https://doi.org/10.1109/icccs55155.2022.9846381","title":"Improving CycleGAN for Image-to-Image Style Transfer by DenseNet","display_name":"Improving CycleGAN for Image-to-Image Style Transfer by DenseNet","publication_year":2022,"publication_date":"2022-04-22","ids":{"openalex":"https://openalex.org/W4291907811","doi":"https://doi.org/10.1109/icccs55155.2022.9846381"},"language":"en","primary_location":{"id":"doi:10.1109/icccs55155.2022.9846381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccs55155.2022.9846381","pdf_url":null,"source":{"id":"https://openalex.org/S4363608130","display_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","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/A5100741699","display_name":"Haoyang Wang","orcid":"https://orcid.org/0000-0001-8236-6628"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haoyang Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Computer Science,Beijing,China","School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Computer Science,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023750777","display_name":"Xiangqun Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangqun Lu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Computer Science,Beijing,China","School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Computer Science,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108050766","display_name":"Fang Deng","orcid":"https://orcid.org/0000-0002-1111-7285"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Deng","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Computer Science,Beijing,China","School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Computer Science,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100741699"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.2399,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.57364894,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"326","last_page":"330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9984999895095825,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9958999752998352,"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":0.8029961585998535},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7419753670692444},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6102216243743896},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5649694204330444},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5387000441551208},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47597044706344604},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4542841911315918},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4529482424259186},{"id":"https://openalex.org/keywords/brightness","display_name":"Brightness","score":0.44760367274284363},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.44494864344596863},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4334127604961395}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8029961585998535},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7419753670692444},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6102216243743896},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5649694204330444},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5387000441551208},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47597044706344604},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4542841911315918},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4529482424259186},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.44760367274284363},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.44494864344596863},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4334127604961395},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccs55155.2022.9846381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccs55155.2022.9846381","pdf_url":null,"source":{"id":"https://openalex.org/S4363608130","display_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2475287302","https://openalex.org/W2962793481","https://openalex.org/W2965417721"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W3192840557","https://openalex.org/W2951211570","https://openalex.org/W4375928479","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W3131673289","https://openalex.org/W4393011546","https://openalex.org/W3198847674"],"abstract_inverted_index":{"With":[0],"the":[1,26,30,40,43,52,61,70,77,98,117,122,127,133,143,150,154,158],"continuous":[2],"progress":[3],"and":[4,46,94,120,132,148,170],"development":[5],"of":[6,25,33,42,72,76,97],"machine":[7],"learning,":[8],"deep":[9,57],"learning":[10],"has":[11,85],"become":[12],"a":[13,56],"hot":[14],"research":[15,27],"field":[16],"today.":[17],"Among":[18],"them,":[19],"image-to-image":[20],"style":[21,35,54,71,80],"transfer":[22,36,69,81],"is":[23,37,74],"one":[24,75],"hotspots.":[28],"Generally,":[29],"main":[31],"goal":[32],"image":[34,45,79,123,144],"to":[38,68,115],"extract":[39],"features":[41],"original":[44,118,134],"convert":[47],"them":[48],"into":[49],"images":[50,73,155],"with":[51],"target":[53],"through":[55,142],"neural":[58],"network.":[59],"Applying":[60],"cycle-consistent":[62],"adversarial":[63],"network":[64,129,136,162],"known":[65],"as":[66,88],"CycleGAN":[67,84,135],"existing":[78],"techniques,":[82],"but":[83],"problems":[86],"such":[87],"insufficient":[89],"brightness":[90],"enhancement,":[91],"color":[92],"distortion,":[93],"low":[95],"authenticity":[96],"generated":[99,125,156],"images.":[100],"To":[101],"address":[102],"this":[103,106],"problem,":[104],"in":[105],"paper,":[107],"we":[108],"construct":[109],"an":[110],"improved":[111,128,159],"CycleGAN,":[112],"use":[113],"DenseNet":[114,131,165],"replace":[116],"ResNet,":[119],"compare":[121],"effects":[124,169],"by":[126,157],"using":[130],"based":[137,163],"on":[138,164],"ResNet.":[139],"After":[140],"calculating":[141],"evaluation":[145],"indicators":[146],"PSNR":[147],"SSIM,":[149],"results":[151],"show":[152],"that":[153],"recurrent":[160],"consistency":[161],"have":[166],"better":[167],"visual":[168],"realism.":[171]},"counts_by_year":[{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}