{"id":"https://openalex.org/W4213114278","doi":"https://doi.org/10.3390/sym14020395","title":"DGAN-KPN: Deep Generative Adversarial Network and Kernel Prediction Network for Denoising MC Renderings","display_name":"DGAN-KPN: Deep Generative Adversarial Network and Kernel Prediction Network for Denoising MC Renderings","publication_year":2022,"publication_date":"2022-02-16","ids":{"openalex":"https://openalex.org/W4213114278","doi":"https://doi.org/10.3390/sym14020395"},"language":"en","primary_location":{"id":"doi:10.3390/sym14020395","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14020395","pdf_url":"https://www.mdpi.com/2073-8994/14/2/395/pdf?version=1645017221","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/2073-8994/14/2/395/pdf?version=1645017221","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071748680","display_name":"Ahmed Mustafa Taha Alzbier","orcid":"https://orcid.org/0000-0002-5446-7859"},"institutions":[{"id":"https://openalex.org/I106645853","display_name":"Changchun University of Science and Technology","ror":"https://ror.org/007mntk44","country_code":"CN","type":"education","lineage":["https://openalex.org/I106645853"]},{"id":"https://openalex.org/I37322517","display_name":"Omdurman Islamic University","ror":"https://ror.org/025qja684","country_code":"SD","type":"education","lineage":["https://openalex.org/I37322517"]}],"countries":["CN","SD"],"is_corresponding":false,"raw_author_name":"Ahmed Mustafa Taha Alzbier","raw_affiliation_strings":["School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China","School of Computer and Information Technology, Omdurman Islamic University, Omdurman 382, Sudan"],"raw_orcid":"https://orcid.org/0000-0002-5446-7859","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China","institution_ids":["https://openalex.org/I106645853"]},{"raw_affiliation_string":"School of Computer and Information Technology, Omdurman Islamic University, Omdurman 382, Sudan","institution_ids":["https://openalex.org/I37322517"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083284188","display_name":"Chunyi Chen","orcid":"https://orcid.org/0000-0003-2228-3083"},"institutions":[{"id":"https://openalex.org/I106645853","display_name":"Changchun University of Science and Technology","ror":"https://ror.org/007mntk44","country_code":"CN","type":"education","lineage":["https://openalex.org/I106645853"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunyi Chen","raw_affiliation_strings":["School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China","institution_ids":["https://openalex.org/I106645853"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083284188"],"corresponding_institution_ids":["https://openalex.org/I106645853"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0979,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.32230478,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"14","issue":"2","first_page":"395","last_page":"395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"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":0.9991000294685364,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983000159263611,"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":0.996999979019165,"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/kernel","display_name":"Kernel (algebra)","score":0.6826198101043701},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6509009599685669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5687772035598755},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5453850030899048},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4898335635662079},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.4621707797050476},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4540761709213257},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43109506368637085},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.42341309785842896},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.41723206639289856},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2852807641029358}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6826198101043701},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6509009599685669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5687772035598755},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5453850030899048},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4898335635662079},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.4621707797050476},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4540761709213257},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43109506368637085},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.42341309785842896},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.41723206639289856},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2852807641029358},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym14020395","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14020395","pdf_url":"https://www.mdpi.com/2073-8994/14/2/395/pdf?version=1645017221","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:098e3be90b0f4a71a2353a55a79f6367","is_oa":true,"landing_page_url":"https://doaj.org/article/098e3be90b0f4a71a2353a55a79f6367","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 14, Iss 2, p 395 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/14/2/395/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym14020395","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; Volume 14; Issue 2; Pages: 395","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym14020395","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14020395","pdf_url":"https://www.mdpi.com/2073-8994/14/2/395/pdf?version=1645017221","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":[{"score":0.6700000166893005,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4213114278.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W2064076387","https://openalex.org/W2133665775","https://openalex.org/W2194775991","https://openalex.org/W2259643685","https://openalex.org/W2331128040","https://openalex.org/W2475287302","https://openalex.org/W2520164769","https://openalex.org/W2737368828","https://openalex.org/W2738449271","https://openalex.org/W2800791979","https://openalex.org/W2811168853","https://openalex.org/W2912646773","https://openalex.org/W2944270038","https://openalex.org/W2948978827","https://openalex.org/W2956015785","https://openalex.org/W2958080091","https://openalex.org/W2963073614","https://openalex.org/W2963200935","https://openalex.org/W2963420272","https://openalex.org/W2963522749","https://openalex.org/W2978132914","https://openalex.org/W2984567007","https://openalex.org/W2999388423","https://openalex.org/W3039049957","https://openalex.org/W3043640841","https://openalex.org/W3105558265","https://openalex.org/W3110029631","https://openalex.org/W3173358655","https://openalex.org/W4200493783","https://openalex.org/W6702130928","https://openalex.org/W6726381175"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2387995142","https://openalex.org/W4380714744","https://openalex.org/W4319453655","https://openalex.org/W2089959425","https://openalex.org/W2057775761","https://openalex.org/W1608433645","https://openalex.org/W2366944513"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,253],"present":[4],"a":[5,10,15,81,170,255],"denoising":[6],"network":[7,13,19,25,28,53,90],"composed":[8],"of":[9,31,180,196,205],"kernel":[11,51,76,83,140,159],"prediction":[12,52,82,139,158],"and":[14,45,74,78,100,123,128,141,156,183,246,252],"deep":[16],"generative":[17],"adversarial":[18,89],"to":[20,149,162,168,184,224],"construct":[21],"an":[22],"end-to-end":[23],"overall":[24],"structure.":[26],"The":[27,50,87,105],"structure":[29,122],"consists":[30],"three":[32],"parts:":[33,96],"the":[34,39,46,56,62,66,70,75,97,101,109,115,119,124,131,138,142,150,157,163,178,181,188,206,210,217,225,230,240],"Kernel":[35],"Prediction":[36],"Network":[37,43],"(KPN),":[38],"Deep":[40],"Generation":[41],"Adversarial":[42],"(DGAN),":[44],"image":[47,60,113,133,146,151,167,192,207,213,221],"reconstruction":[48,152,208],"model.":[49,104],"model":[54,91,99,107,153],"takes":[55,108],"auxiliary":[57],"feature":[58,71],"information":[59,68,72],"as":[61,114,216],"input,":[63,116],"passes":[64,117],"through":[65,118],"source":[67],"encoder,":[69,73],"predictor,":[77],"finally":[79,129],"generates":[80],"for":[84,154,198],"each":[85],"pixel.":[86],"generated":[88],"is":[92,147,160,214,222],"divided":[93],"into":[94],"two":[95],"generator":[98,106],"multiscale":[102],"discriminator":[103],"noisy":[110],"Monte":[111],"Carlo-rendered":[112],"symmetric":[120],"encoder\u2013decoder":[121],"residual":[125],"block":[126],"structure,":[127],"outputs":[130],"rendered":[132,145,166,191],"with":[134,235],"preliminary":[135],"denoising.":[136,200],"Then,":[137],"preliminarily":[143,164,171],"denoised":[144,165,212,220],"sent":[148],"reconstruction,":[155],"applied":[161,223],"obtain":[169],"reconstructed":[172,190],"result":[173,182],"image.":[174],"To":[175],"further":[176,199],"improve":[177],"quality":[179],"be":[185],"more":[186],"robust,":[187],"initially":[189],"undergoes":[193],"four":[194,203],"iterations":[195,204],"filtering":[197],"Finally,":[201],"after":[202],"model,":[209],"final":[211],"presented":[215],"output.":[218],"This":[219],"loss":[226],"function.":[227],"We":[228],"compared":[229],"results":[231,237],"from":[232],"our":[233],"approach":[234],"state-of-the-art":[236],"by":[238],"using":[239],"structural":[241],"similarity":[242],"index":[243],"(SSIM)":[244],"values":[245],"peak":[247],"signal-to-noise":[248],"ratio":[249],"(PSNR)":[250],"values,":[251],"reported":[254],"better":[256],"performance.":[257]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2022-02-24T00:00:00"}
