{"id":"https://openalex.org/W4386246940","doi":"https://doi.org/10.1145/3599957.3606243","title":"Optimizing Generative Adversarial Networks Models for Non-Pneumatic Tire Design","display_name":"Optimizing Generative Adversarial Networks Models for Non-Pneumatic Tire Design","publication_year":2023,"publication_date":"2023-08-06","ids":{"openalex":"https://openalex.org/W4386246940","doi":"https://doi.org/10.1145/3599957.3606243"},"language":"en","primary_location":{"id":"doi:10.1145/3599957.3606243","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3599957.3606243","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","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/A5092814966","display_name":"JuYong Seong","orcid":"https://orcid.org/0009-0003-9511-5651"},"institutions":[{"id":"https://openalex.org/I51926615","display_name":"Sun Moon University","ror":"https://ror.org/009e5cd49","country_code":"KR","type":"education","lineage":["https://openalex.org/I51926615"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Ju-Yong Seong","raw_affiliation_strings":["Division of Computer Science and Engineering, Sunmoon University, Asan-si, Chungcheongnam-do, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0003-9511-5651","affiliations":[{"raw_affiliation_string":"Division of Computer Science and Engineering, Sunmoon University, Asan-si, Chungcheongnam-do, Republic of Korea","institution_ids":["https://openalex.org/I51926615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030580369","display_name":"S. Ji","orcid":"https://orcid.org/0009-0002-3503-9581"},"institutions":[{"id":"https://openalex.org/I51926615","display_name":"Sun Moon University","ror":"https://ror.org/009e5cd49","country_code":"KR","type":"education","lineage":["https://openalex.org/I51926615"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seung-min Ji","raw_affiliation_strings":["Division of Computer Science and Engineering, Sunmoon University, Asan-si, Chungcheongnam-do, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0002-3503-9581","affiliations":[{"raw_affiliation_string":"Division of Computer Science and Engineering, Sunmoon University, Asan-si, Chungcheongnam-do, Republic of Korea","institution_ids":["https://openalex.org/I51926615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101439512","display_name":"Daehyeon Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I51926615","display_name":"Sun Moon University","ror":"https://ror.org/009e5cd49","country_code":"KR","type":"education","lineage":["https://openalex.org/I51926615"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong-hyun Choi","raw_affiliation_strings":["Department of Artificial Intelligence and Software Technology Sunmoon University Asan-si, Chungcheongnam-do, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0008-6020-3471","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Software Technology Sunmoon University Asan-si, Chungcheongnam-do, Republic of Korea","institution_ids":["https://openalex.org/I51926615"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008179235","display_name":"Sungchul Lee","orcid":"https://orcid.org/0000-0001-7790-4102"},"institutions":[{"id":"https://openalex.org/I51926615","display_name":"Sun Moon University","ror":"https://ror.org/009e5cd49","country_code":"KR","type":"education","lineage":["https://openalex.org/I51926615"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sungchul Lee","raw_affiliation_strings":["Division of Computer Science and Engineering, Sunmoon University, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0001-7790-4102","affiliations":[{"raw_affiliation_string":"Division of Computer Science and Engineering, Sunmoon University, Republic of Korea","institution_ids":["https://openalex.org/I51926615"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5092814966"],"corresponding_institution_ids":["https://openalex.org/I51926615"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0964736,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9922000169754028,"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":0.9922000169754028,"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":0.9800000190734863,"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":0.9666000008583069,"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/similarity","display_name":"Similarity (geometry)","score":0.7314257025718689},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6986638307571411},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6425564289093018},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5633075833320618},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5462945103645325},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5318545699119568},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5174294114112854},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.514460563659668},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.48341572284698486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48194026947021484},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.4468657374382019},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3643624186515808},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30863451957702637},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2564260959625244},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24935781955718994},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1467224657535553}],"concepts":[{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7314257025718689},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6986638307571411},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6425564289093018},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5633075833320618},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5462945103645325},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5318545699119568},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5174294114112854},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.514460563659668},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.48341572284698486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48194026947021484},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.4468657374382019},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3643624186515808},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30863451957702637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2564260959625244},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24935781955718994},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1467224657535553},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3599957.3606243","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3599957.3606243","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2085963752","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2194775991","https://openalex.org/W2618530766","https://openalex.org/W2766086266","https://openalex.org/W2962770929","https://openalex.org/W2962785568","https://openalex.org/W3096831136","https://openalex.org/W4205199447","https://openalex.org/W4285981784","https://openalex.org/W4286869901","https://openalex.org/W6803132585"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W2888032422","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/W4235873501"],"abstract_inverted_index":{"Pneumatic":[0],"tires1":[1],"are":[2,12],"used":[3,50],"in":[4,26],"a":[5,116],"wide":[6],"range":[7],"of":[8,21,29,37,74],"industries.":[9],"However,":[10],"they":[11],"difficult":[13],"to":[14],"design":[15,28],"and":[16,61,88,92,101,112,127,155],"rely":[17],"on":[18],"the":[19,27,35,68,95,98,107,123,128,134,150,153],"knowledge":[20],"experienced":[22],"designers.":[23],"To":[24,66],"aid":[25],"pneumatic":[30],"tires,":[31,78],"this":[32],"paper":[33],"suggests":[34],"use":[36],"Generative":[38,82],"Adversarial":[39,83],"Networks":[40,84],"(GAN)":[41],"models.":[42,137],"The":[43],"2000":[44],"created":[45],"images":[46,55],"for":[47,71],"training":[48],"were":[49,90],"after":[51],"removing":[52],"highly":[53],"sim-ilar":[54],"using":[56],"Mean":[57],"Squared":[58],"Error":[59],"(MSE)":[60],"Structural":[62],"Similarity":[63],"Index":[64],"(SSIM).":[65],"find":[67],"best":[69,144],"model":[70],"generating":[72],"patterns":[73],"regularly":[75],"shaped":[76],"non-pneumatic":[77],"GAN,":[79,99],"Deep":[80],"Convolu-tional":[81],"(DCGAN),":[85],"StyleGANv2":[86],"ADA":[87],"ProjectedGAN":[89,120,142],"compared":[91],"analyzed.":[93],"In":[94],"qualitative":[96],"evaluation,":[97],"DCGAN,":[100],"StyleGAN":[102],"v2-ADA":[103],"models":[104],"showed":[105,121],"that":[106,122,148],"circle":[108,124],"shape":[109],"was":[110,130],"distorted":[111,132],"did":[113],"not":[114],"maintain":[115],"consistent":[117,126],"pattern,":[118],"but":[119],"remained":[125],"pattern":[129],"less":[131],"than":[133],"other":[135],"GAN":[136],"When":[138],"evaluating":[139],"quantitative":[140],"metrics,":[141],"performed":[143],"among":[145],"several":[146],"techniques":[147],"measure":[149],"difference":[151],"be-tween":[152],"generated":[154],"actual":[156],"image":[157],"distributions.":[158]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}