{"id":"https://openalex.org/W4309089739","doi":"https://doi.org/10.3390/sym14112295","title":"Image Colorization Algorithm Based on Deep Learning","display_name":"Image Colorization Algorithm Based on Deep Learning","publication_year":2022,"publication_date":"2022-11-02","ids":{"openalex":"https://openalex.org/W4309089739","doi":"https://doi.org/10.3390/sym14112295"},"language":"en","primary_location":{"id":"doi:10.3390/sym14112295","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14112295","pdf_url":"https://www.mdpi.com/2073-8994/14/11/2295/pdf?version=1667378394","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/14/11/2295/pdf?version=1667378394","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100461427","display_name":"Na Wang","orcid":"https://orcid.org/0000-0002-9786-8548"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Wang","raw_affiliation_strings":["Engineering Research Center for ICH Digitalization and Multi-Source Information Fusion (Fujian Polytechnic Normal University), Fujian Province University, Fuzhou 350300, China","School of Big Data and Artificial Intelligence, Fujian Polytechnic Normal University, Fuzhou 350300, China"],"affiliations":[{"raw_affiliation_string":"Engineering Research Center for ICH Digitalization and Multi-Source Information Fusion (Fujian Polytechnic Normal University), Fujian Province University, Fuzhou 350300, China","institution_ids":["https://openalex.org/I111753288"]},{"raw_affiliation_string":"School of Big Data and Artificial Intelligence, Fujian Polytechnic Normal University, Fuzhou 350300, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067992824","display_name":"Guodong Chen","orcid":"https://orcid.org/0000-0002-4835-708X"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guo-Dong Chen","raw_affiliation_strings":["College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China"],"affiliations":[{"raw_affiliation_string":"College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100692636","display_name":"Ying Tian","orcid":"https://orcid.org/0000-0002-6031-2335"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Tian","raw_affiliation_strings":["College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China"],"affiliations":[{"raw_affiliation_string":"College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5067992824"],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":1.1216,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.79138854,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"14","issue":"11","first_page":"2295","last_page":"2295"},"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":0.9905999898910522,"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":0.9905999898910522,"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":0.9282000064849854,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9067999720573425,"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":0.7663615942001343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7020219564437866},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5937316417694092},{"id":"https://openalex.org/keywords/activation-function","display_name":"Activation function","score":0.5361509323120117},{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.4759140610694885},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4491616487503052},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.44282615184783936},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4213232398033142},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4019573926925659},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3993924856185913},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3756850063800812},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3549680709838867}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7663615942001343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7020219564437866},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5937316417694092},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.5361509323120117},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.4759140610694885},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4491616487503052},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.44282615184783936},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4213232398033142},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4019573926925659},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3993924856185913},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3756850063800812},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3549680709838867},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym14112295","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14112295","pdf_url":"https://www.mdpi.com/2073-8994/14/11/2295/pdf?version=1667378394","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:949922bb3e6047719a5bafc3372d62bf","is_oa":true,"landing_page_url":"https://doaj.org/article/949922bb3e6047719a5bafc3372d62bf","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 14, Iss 11, p 2295 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/14/11/2295/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym14112295","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym14112295","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14112295","pdf_url":"https://www.mdpi.com/2073-8994/14/11/2295/pdf?version=1667378394","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4309089739.pdf","grobid_xml":"https://content.openalex.org/works/W4309089739.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W2005690024","https://openalex.org/W2025328853","https://openalex.org/W2104853049","https://openalex.org/W2117539524","https://openalex.org/W2120963736","https://openalex.org/W2121579674","https://openalex.org/W2129112648","https://openalex.org/W2136154655","https://openalex.org/W2160341927","https://openalex.org/W2169321544","https://openalex.org/W2295537950","https://openalex.org/W2308529009","https://openalex.org/W2326925005","https://openalex.org/W2408359267","https://openalex.org/W2461158874","https://openalex.org/W2511951438","https://openalex.org/W2552619376","https://openalex.org/W2560481159","https://openalex.org/W2590274298","https://openalex.org/W2599541538","https://openalex.org/W2612063021","https://openalex.org/W2768083292","https://openalex.org/W2768918307","https://openalex.org/W2771042329","https://openalex.org/W2803955021","https://openalex.org/W2804918468","https://openalex.org/W2891828576","https://openalex.org/W2963181089","https://openalex.org/W3000407986","https://openalex.org/W3000626837","https://openalex.org/W3002483502","https://openalex.org/W3034838697","https://openalex.org/W3092686490","https://openalex.org/W3112102355","https://openalex.org/W3135725160","https://openalex.org/W4213258551","https://openalex.org/W4220815429","https://openalex.org/W4285392998","https://openalex.org/W6646938681","https://openalex.org/W6737325397","https://openalex.org/W7052046445"],"related_works":["https://openalex.org/W2032258609","https://openalex.org/W3024979424","https://openalex.org/W4283785902","https://openalex.org/W3032499992","https://openalex.org/W2041004593","https://openalex.org/W3134817226","https://openalex.org/W2895192346","https://openalex.org/W3110577345","https://openalex.org/W3136579697","https://openalex.org/W2811324119"],"abstract_inverted_index":{"As":[0],"we":[1,142],"know,":[2],"image":[3,21,24,119,179],"colorization":[4,25,180],"is":[5,38,61],"widely":[6],"used":[7],"in":[8,17,114],"computer":[9],"graphics":[10],"and":[11,34,44,71,79,97,103,111,128,136,147,163,196],"has":[12,27],"become":[13],"a":[14,52,57,105],"research":[15],"hotspot":[16],"the":[18,28,65,73,76,80,85,100,118,125,144,149,155,165,170,184,190,194],"field":[19],"of":[20,30,68,75,82,95,133,139,193],"processing.":[22],"Current":[23],"technology":[26],"phenomenon":[29],"single":[31],"coloring":[32,67,77,83],"effect":[33,78],"unreal":[35],"color,":[36],"which":[37],"too":[39],"complicated":[40],"to":[41,46,63,116,153],"be":[42],"implemented":[43],"struggled":[45],"gain":[47],"popularity.":[48],"In":[49],"this":[50,89,122],"paper,":[51],"new":[53],"method":[54],"based":[55,182],"on":[56,183],"convolution":[58],"neural":[59],"network":[60,127,195],"proposed":[62,178],"study":[64],"reasonable":[66],"human":[69],"images":[70],"ensures":[72],"realism":[74],"diversity":[81],"at":[84],"same":[86],"time.":[87],"First,":[88],"paper":[90,123],"selects":[91],"about":[92],"5000":[93],"pictures":[94],"people":[96,110],"plants":[98],"from":[99],"Imagenet":[101],"dataset":[102,107],"makes":[104],"small":[106],"containing":[108],"only":[109],"backgrounds.":[112],"Secondly,":[113],"order":[115],"obtain":[117],"segmentation":[120,200],"results,":[121],"improves":[124],"U-net":[126],"carries":[129],"out":[130],"three":[131,137],"times":[132,138],"down":[134],"sampling":[135],"up-sampling.":[140],"Finally,":[141],"add":[143],"expanded":[145],"convolution,":[146],"use":[148],"sigmoid":[150],"activation":[151,161,171],"function":[152,162],"replace":[154],"ReLU":[156],"(The":[157],"Rectified":[158],"Linear":[159],"Unit)":[160],"put":[164],"BN":[166],"(Batch":[167],"Normalization)":[168],"before":[169],"function.":[172],"Experimental":[173],"results":[174],"show":[175],"that":[176],"our":[177],"algorithm":[181],"deep":[185],"learning":[186],"scheme":[187],"can":[188],"reduce":[189],"training":[191],"time":[192],"achieve":[197],"higher":[198],"quality":[199],"results.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}