{"id":"https://openalex.org/W3015860739","doi":"https://doi.org/10.1109/icassp40776.2020.9054432","title":"Gray-Scale Image Colorization Using Cycle-Consistent Generative Adversarial Networks with Residual Structure Enhancer","display_name":"Gray-Scale Image Colorization Using Cycle-Consistent Generative Adversarial Networks with Residual Structure Enhancer","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015860739","doi":"https://doi.org/10.1109/icassp40776.2020.9054432","mag":"3015860739"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5072981504","display_name":"Mohammad Mahdi Johari","orcid":"https://orcid.org/0000-0002-1996-9837"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Mohammad Mahdi Johari","raw_affiliation_strings":["Electrical Engineering Department, Sharif University of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051416738","display_name":"Hamid Behroozi","orcid":"https://orcid.org/0000-0001-9294-3134"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Hamid Behroozi","raw_affiliation_strings":["Electrical Engineering Department, Sharif University of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5072981504"],"corresponding_institution_ids":["https://openalex.org/I133529467"],"apc_list":null,"apc_paid":null,"fwci":0.3908,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60311219,"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":"2223","last_page":"2227"},"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":0.9976999759674072,"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":0.9976999759674072,"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":0.9921000003814697,"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":0.9901000261306763,"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/image-translation","display_name":"Image translation","score":0.8398224115371704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7366898059844971},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7209365367889404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.685217022895813},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6330904364585876},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6279077529907227},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.4948224425315857},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.474132776260376},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4725453853607178},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4197290241718292},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.351984441280365},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3025132417678833},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07093465328216553}],"concepts":[{"id":"https://openalex.org/C2779757391","wikidata":"https://www.wikidata.org/wiki/Q6002292","display_name":"Image translation","level":3,"score":0.8398224115371704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7366898059844971},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7209365367889404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.685217022895813},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6330904364585876},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6279077529907227},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.4948224425315857},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.474132776260376},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4725453853607178},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4197290241718292},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.351984441280365},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3025132417678833},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07093465328216553},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1580389772","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W2095705004","https://openalex.org/W2099471712","https://openalex.org/W2117539524","https://openalex.org/W2133665775","https://openalex.org/W2194775991","https://openalex.org/W2295537950","https://openalex.org/W2308529009","https://openalex.org/W2326925005","https://openalex.org/W2402144811","https://openalex.org/W2461158874","https://openalex.org/W2590274298","https://openalex.org/W2593414223","https://openalex.org/W2598581049","https://openalex.org/W2792021479","https://openalex.org/W2904843110","https://openalex.org/W2920598519","https://openalex.org/W2949117887","https://openalex.org/W2951939904","https://openalex.org/W2953384591","https://openalex.org/W2962793481","https://openalex.org/W2962903125","https://openalex.org/W2963073614","https://openalex.org/W2963444790","https://openalex.org/W2963649420","https://openalex.org/W2964121744","https://openalex.org/W3102726805","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6674330103","https://openalex.org/W6698507324","https://openalex.org/W6701655646","https://openalex.org/W6713134421","https://openalex.org/W6734564793","https://openalex.org/W6735204497"],"related_works":["https://openalex.org/W4288069866","https://openalex.org/W4389232935","https://openalex.org/W3155045749","https://openalex.org/W2905311601","https://openalex.org/W2936127876","https://openalex.org/W4387421677","https://openalex.org/W4213477128","https://openalex.org/W2957407072","https://openalex.org/W4312511225","https://openalex.org/W4281776416"],"abstract_inverted_index":{"The":[0,106],"colorization":[1],"of":[2],"gray-scale":[3,37],"images":[4,40],"has":[5],"always":[6],"been":[7,18],"a":[8,47,63,82,87,98],"challenging":[9],"task":[10],"in":[11],"computer":[12],"vision.":[13],"Recently,":[14],"novel":[15],"approaches":[16],"have":[17],"introduced":[19],"for":[20],"unsupervised":[21],"image":[22,59,78],"translation":[23],"between":[24],"two":[25,42,95],"domains":[26],"using":[27],"Generative":[28],"Adversarial":[29],"Networks":[30],"(GANs).":[31],"Since":[32],"one":[33],"can":[34],"consider":[35],"the":[36,69,73,76,112,116,124],"and":[38,115],"colorful":[39],"as":[41],"separate":[43],"domains,":[44],"we":[45],"propose":[46],"two-stage":[48],"cycle-consistent":[49,99],"network":[50,84],"architecture":[51,100],"to":[52],"produce":[53],"convincible":[54],"images.":[55],"First,":[56],"an":[57],"intermediate":[58,77],"is":[60,79,101,109],"generated":[61],"with":[62,86,123],"relatively":[64],"uncomplicated":[65],"objective":[66,90],"function":[67],"at":[68,72,103],"output.":[70],"Next,":[71],"second":[74],"stage,":[75],"enhanced":[80],"via":[81],"residual":[83],"structure":[85],"more":[88],"complicated":[89],"function.":[91],"Furthermore,":[92],"by":[93],"employing":[94],"inverse":[96],"networks,":[97],"formed":[102],"both":[104],"stages.":[105],"proposed":[107],"model":[108],"trained":[110],"on":[111],"ImageNet":[113],"dataset,":[114],"achieved":[117],"outcomes":[118],"demonstrate":[119],"exceptional":[120],"performance":[121],"comparing":[122],"state-of-the-art":[125],"models.":[126]},"counts_by_year":[{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
