{"id":"https://openalex.org/W4404238882","doi":"https://doi.org/10.1109/icstcc62912.2024.10744742","title":"Colouring Grayscale Images Using Cycle-Generative-Adversarial Networks","display_name":"Colouring Grayscale Images Using Cycle-Generative-Adversarial Networks","publication_year":2024,"publication_date":"2024-10-10","ids":{"openalex":"https://openalex.org/W4404238882","doi":"https://doi.org/10.1109/icstcc62912.2024.10744742"},"language":"en","primary_location":{"id":"doi:10.1109/icstcc62912.2024.10744742","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icstcc62912.2024.10744742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 28th International Conference on System Theory, Control and Computing (ICSTCC)","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/A5114592684","display_name":"Radu-Cosmin Hobinc\u0103","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108695","display_name":"Gheorghe Asachi Technical University of Ia\u0219i","ror":"https://ror.org/014zxnz40","country_code":"RO","type":"education","lineage":["https://openalex.org/I4210108695"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Radu-Cosmin Hobinc\u0103","raw_affiliation_strings":["\"Gheorghe Asachi\" Technical University of Ia&#x015F;i,Department of Automatic Control and Applied Informatics,Iasi,Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\"Gheorghe Asachi\" Technical University of Ia&#x015F;i,Department of Automatic Control and Applied Informatics,Iasi,Romania","institution_ids":["https://openalex.org/I4210108695"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085283008","display_name":"Lavinia Ferariu","orcid":"https://orcid.org/0000-0001-5758-6696"},"institutions":[{"id":"https://openalex.org/I4210108695","display_name":"Gheorghe Asachi Technical University of Ia\u0219i","ror":"https://ror.org/014zxnz40","country_code":"RO","type":"education","lineage":["https://openalex.org/I4210108695"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Lavinia-Eugenia Ferariu","raw_affiliation_strings":["\"Gheorghe Asachi\" Technical University of Ia&#x015F;i,Department of Automatic Control and Applied Informatics,Iasi,Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\"Gheorghe Asachi\" Technical University of Ia&#x015F;i,Department of Automatic Control and Applied Informatics,Iasi,Romania","institution_ids":["https://openalex.org/I4210108695"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18425412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"101","last_page":"106"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.8610000014305115,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.8610000014305115,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7786999940872192,"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/T11666","display_name":"Color Science and Applications","score":0.7520999908447266,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.9181816577911377},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7865337133407593},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7301987409591675},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6819791793823242},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5448141694068909},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4981851577758789},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4617924690246582},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.45788586139678955},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3363233804702759}],"concepts":[{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.9181816577911377},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7865337133407593},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7301987409591675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6819791793823242},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5448141694068909},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4981851577758789},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4617924690246582},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.45788586139678955},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3363233804702759}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icstcc62912.2024.10744742","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icstcc62912.2024.10744742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 28th International Conference on System Theory, Control and Computing (ICSTCC)","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":15,"referenced_works":["https://openalex.org/W2245625259","https://openalex.org/W2326925005","https://openalex.org/W2461158874","https://openalex.org/W2798401174","https://openalex.org/W2954360087","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W3010626953","https://openalex.org/W3159396579","https://openalex.org/W4318263505","https://openalex.org/W4320013936","https://openalex.org/W4324137776","https://openalex.org/W4380301071","https://openalex.org/W4386813775","https://openalex.org/W4401717981"],"related_works":["https://openalex.org/W2888032422","https://openalex.org/W2996316059","https://openalex.org/W4385421777","https://openalex.org/W4377980832","https://openalex.org/W2897769091","https://openalex.org/W2845413374","https://openalex.org/W3005996785","https://openalex.org/W4297411772","https://openalex.org/W4283758926","https://openalex.org/W4235873501"],"abstract_inverted_index":{"This":[0],"paper":[1],"analyses":[2],"models":[3],"that":[4],"can":[5],"realistically":[6],"map":[7],"the":[8,13,39,48],"grayscale":[9],"image":[10,15,51,59],"domain":[11],"to":[12,34,55,78,114,134],"color":[14,74,81,87],"domain.":[16],"We":[17,71],"thus":[18],"focus":[19],"our":[20,128],"attention":[21],"on":[22],"a":[23,73,111,131],"CycleGAN":[24,57],"(Cycle-consistent":[25],"Generative":[26],"Adversarial":[27],"Network)":[28],"neural":[29],"network":[30,113],"architecture,":[31],"which":[32],"proves":[33],"have":[35],"good":[36],"results":[37],"in":[38,47,86],"area":[40],"of":[41,50,95],"translation":[42],"between":[43,89],"domains,":[44],"and":[45,137],"implicitly":[46],"application":[49],"coloring.":[52],"In":[53],"addition":[54],"exploring":[56],"for":[58],"colorization,":[60],"this":[61,107],"study":[62],"introduces":[63],"novel":[64],"techniques":[65],"aimed":[66],"at":[67],"enhancing":[68],"its":[69],"performance.":[70],"incorporate":[72],"distribution":[75,88],"loss":[76],"term":[77],"ensure":[79],"reliable":[80],"mapping,":[82],"effectively":[83],"addressing":[84],"discrepancies":[85],"domains.":[90],"Moreover,":[91],"an":[92],"in-depth":[93],"analysis":[94],"generator":[96],"errors":[97],"is":[98],"conducted,":[99],"unveiling":[100],"critical":[101],"insights":[102],"into":[103],"model":[104],"limitations.":[105],"Leveraging":[106],"analysis,":[108],"we":[109],"propose":[110],"correction":[112],"generate":[115],"residual":[116],"images,":[117],"facilitating":[118],"more":[119],"accurate":[120],"colorization.":[121],"Through":[122],"rigorous":[123],"experimentation":[124],"across":[125],"diverse":[126],"datasets,":[127],"approach":[129],"showcases":[130],"remarkable":[132],"capacity":[133],"produce":[135],"lifelike":[136],"coherent":[138],"colorizations.":[139]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
