{"id":"https://openalex.org/W2990440529","doi":"https://doi.org/10.1109/tnnls.2020.3045000","title":"Simple Yet Effective Way for Improving the Performance of GAN","display_name":"Simple Yet Effective Way for Improving the Performance of GAN","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W2990440529","doi":"https://doi.org/10.1109/tnnls.2020.3045000","mag":"2990440529","pmid":"https://pubmed.ncbi.nlm.nih.gov/33385312"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2020.3045000","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3045000","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1911.10979","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016485454","display_name":"Yoon-Jae Yeo","orcid":"https://orcid.org/0000-0002-1366-2973"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yoon-Jae Yeo","raw_affiliation_strings":["School of Electrical Engineering Department, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering Department, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043424455","display_name":"Yong-Goo Shin","orcid":"https://orcid.org/0000-0002-2189-3886"},"institutions":[{"id":"https://openalex.org/I112728665","display_name":"Hannam University","ror":"https://ror.org/01cwbae71","country_code":"KR","type":"education","lineage":["https://openalex.org/I112728665"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yong-Goo Shin","raw_affiliation_strings":["Division of Smart Interdisciplinary Engineering, Hannam University, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"Division of Smart Interdisciplinary Engineering, Hannam University, Daejeon, South Korea","institution_ids":["https://openalex.org/I112728665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069241394","display_name":"Seung Park","orcid":"https://orcid.org/0000-0003-2311-9306"},"institutions":[{"id":"https://openalex.org/I2802194831","display_name":"Samsung Medical Center","ror":"https://ror.org/05a15z872","country_code":"KR","type":"healthcare","lineage":["https://openalex.org/I2250650973","https://openalex.org/I2802194831"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seung Park","raw_affiliation_strings":["Medical AI Center, Samsung Medical Center, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Medical AI Center, Samsung Medical Center, Seoul, South Korea","institution_ids":["https://openalex.org/I2802194831"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020023785","display_name":"Sung-Jea Ko","orcid":"https://orcid.org/0000-0002-4875-7091"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sung-Jea Ko","raw_affiliation_strings":["School of Electrical Engineering Department, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering Department, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016485454"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":2.1315,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.88992447,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"33","issue":"4","first_page":"1811","last_page":"1818"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9997000098228455,"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":0.9954000115394592,"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/discriminator","display_name":"Discriminator","score":0.9847805500030518},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7321822643280029},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.7192078232765198},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.7173904180526733},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5639183521270752},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5613529086112976},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.4586586356163025},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44707056879997253},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43827587366104126},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4060443043708801}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.9847805500030518},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7321822643280029},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.7192078232765198},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.7173904180526733},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5639183521270752},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5613529086112976},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.4586586356163025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44707056879997253},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43827587366104126},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4060443043708801},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2020.3045000","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3045000","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:33385312","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33385312","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:arXiv.org:1911.10979","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.10979","pdf_url":"https://arxiv.org/pdf/1911.10979","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1911.10979","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.10979","pdf_url":"https://arxiv.org/pdf/1911.10979","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W967544008","https://openalex.org/W1522301498","https://openalex.org/W1834627138","https://openalex.org/W2099471712","https://openalex.org/W2108598243","https://openalex.org/W2125389028","https://openalex.org/W2145607950","https://openalex.org/W2163605009","https://openalex.org/W2173520492","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2405756170","https://openalex.org/W2412510955","https://openalex.org/W2502312327","https://openalex.org/W2545656684","https://openalex.org/W2548275288","https://openalex.org/W2564591810","https://openalex.org/W2766527293","https://openalex.org/W2782980316","https://openalex.org/W2785678896","https://openalex.org/W2787579267","https://openalex.org/W2804078698","https://openalex.org/W2807633959","https://openalex.org/W2947622416","https://openalex.org/W2949999304","https://openalex.org/W2950776302","https://openalex.org/W2950893734","https://openalex.org/W2953327099","https://openalex.org/W2962793481","https://openalex.org/W2962879692","https://openalex.org/W2963073614","https://openalex.org/W2963163163","https://openalex.org/W2963306805","https://openalex.org/W2963373786","https://openalex.org/W2963398989","https://openalex.org/W2963563295","https://openalex.org/W2963684088","https://openalex.org/W2963767194","https://openalex.org/W2963981733","https://openalex.org/W2964024144","https://openalex.org/W2964216930","https://openalex.org/W2979557588","https://openalex.org/W2982763192","https://openalex.org/W3011708679","https://openalex.org/W4293775665","https://openalex.org/W4294643831","https://openalex.org/W4295521014","https://openalex.org/W4296979096","https://openalex.org/W4297606427","https://openalex.org/W4301206121","https://openalex.org/W4320013936","https://openalex.org/W4394670483","https://openalex.org/W6625168331","https://openalex.org/W6631190155","https://openalex.org/W6678815747","https://openalex.org/W6684191040","https://openalex.org/W6685352114","https://openalex.org/W6713645886","https://openalex.org/W6715189028","https://openalex.org/W6718379498","https://openalex.org/W6729110096","https://openalex.org/W6729482032","https://openalex.org/W6735913928","https://openalex.org/W6745560452","https://openalex.org/W6747733185","https://openalex.org/W6748582592","https://openalex.org/W6748655329","https://openalex.org/W6752378368","https://openalex.org/W6752670383","https://openalex.org/W6765779288","https://openalex.org/W6779669310"],"related_works":["https://openalex.org/W4293320219","https://openalex.org/W2953246223","https://openalex.org/W3110074278","https://openalex.org/W4283584549","https://openalex.org/W2618858825","https://openalex.org/W2554314924","https://openalex.org/W2998859928","https://openalex.org/W4308217387","https://openalex.org/W3180903229","https://openalex.org/W2986089616"],"abstract_inverted_index":{"In":[0,117],"adversarial":[1,44],"learning,":[2],"the":[3,9,39,42,49,54,82,87,92,99,103,114,120,158,163,173,179,185],"discriminator":[4,93,100],"often":[5],"fails":[6],"to":[7,106,113,136],"guide":[8,102],"generator":[10,104],"successfully":[11],"since":[12,119],"it":[13,131],"distinguishes":[14],"between":[15],"real":[16,115],"and":[17,154,167,181],"generated":[18,186],"images":[19,108],"using":[20,81],"silly":[21],"or":[22,52],"nonrobust":[23],"features.":[24],"To":[25],"alleviate":[26],"this":[27,29],"problem,":[28],"brief":[30],"presents":[31],"a":[32,64,126],"simple":[33,128],"but":[34],"effective":[35],"way":[36],"that":[37,109,157],"improves":[38,162],"performance":[40,164],"of":[41,57,165,172,184],"generative":[43],"network":[45,55],"(GAN)":[46],"without":[47],"imposing":[48],"training":[50,141],"overhead":[51],"modifying":[53],"architectures":[56],"existing":[58,137],"methods.":[59],"The":[60],"proposed":[61,121,159],"method":[62,160],"employs":[63],"novel":[65],"cascading":[66],"rejection":[67,84],"(CR)":[68],"module":[69,123],"for":[70],"discriminator,":[71],"which":[72],"extracts":[73],"multiple":[74],"nonoverlapped":[75],"features":[76,90],"in":[77,170],"an":[78],"iterative":[79],"manner":[80],"vector":[83,129],"operation.":[85],"Since":[86],"extracted":[88],"diverse":[89],"prevent":[91],"from":[94],"concentrating":[95],"on":[96,145],"nonmeaningful":[97],"features,":[98],"can":[101,132],"effectively":[105],"produce":[107],"are":[110],"more":[111],"similar":[112],"images.":[116,187],"addition,":[118],"CR":[122],"requires":[124],"only":[125],"few":[127],"operations,":[130],"be":[133],"readily":[134],"applied":[135],"frameworks":[138],"with":[139],"marginal":[140],"overheads.":[142],"Quantitative":[143],"evaluations":[144],"various":[146],"data":[147],"sets,":[148],"including":[149],"CIFAR-10,":[150],"CelebA,":[151],"CelebA-HQ,":[152],"LSUN,":[153],"tiny-ImageNet,":[155],"confirm":[156],"significantly":[161],"GAN":[166,169],"conditional":[168],"terms":[171],"Frechet":[174],"inception":[175],"distance":[176],"(FID),":[177],"indicating":[178],"diversity":[180],"visual":[182],"appearance":[183]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
