{"id":"https://openalex.org/W7214911753","doi":"https://doi.org/10.21872/annual2025_9071","title":"Surface Image Generation Using Conditional GAN for Vision-Based Quality Modeling in Turning Process","display_name":"Surface Image Generation Using Conditional GAN for Vision-Based Quality Modeling in Turning Process","publication_year":2026,"publication_date":"2026-09-30","ids":{"openalex":"https://openalex.org/W7214911753","doi":"https://doi.org/10.21872/annual2025_9071"},"language":"en","primary_location":{"id":"doi:10.21872/annual2025_9071","doi":"https://doi.org/10.21872/annual2025_9071","is_oa":false,"landing_page_url":"https://doi.org/10.21872/annual2025_9071","pdf_url":null,"source":{"id":"https://openalex.org/S7407087832","display_name":"IISE Annual Conference & Expo","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IISE Annual Conference &amp; Expo 2025","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5153570896","display_name":"Haozhou Zhou","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haozhou Zhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5153636973","display_name":"Srinivasan Radhakrishnan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Srinivasan Radhakrishnan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135177087","display_name":"Sagar Kamarthi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sagar Kamarthi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.79596429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10188","display_name":"Advanced machining processes and optimization","score":0.9053000211715698,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10188","display_name":"Advanced machining processes and optimization","score":0.9053000211715698,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.049800001084804535,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.01119999960064888,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"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/surface-roughness","display_name":"surface roughness","score":0.9079999923706055},{"id":"https://openalex.org/keywords/turning","display_name":"turning","score":0.9470000267028809},{"id":"https://openalex.org/keywords/conditional-gan","display_name":"conditional generative adversarial networks","score":0.9309999942779541},{"id":"https://openalex.org/keywords/aisi-1018-steel","display_name":"AISI 1018 steel","score":0.800000011920929},{"id":"https://openalex.org/keywords/feed-rate","display_name":"feed rate","score":0.8069999814033508},{"id":"https://openalex.org/keywords/depth-of-cut","display_name":"depth of cut","score":1.0},{"id":"https://openalex.org/keywords/training-data-generation","display_name":"training data generation","score":0.640999972820282},{"id":"https://openalex.org/keywords/surface-finish","display_name":"surface finish","score":0.4869999885559082}],"concepts":[{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.7142000198364258},{"id":"https://openalex.org/C107365816","wikidata":"https://www.wikidata.org/wiki/Q114817","display_name":"Surface roughness","level":2,"score":0.6978999972343445},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.6603999733924866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5340999960899353},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.51419997215271},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5031999945640564},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4837000072002411},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46459999680519104},{"id":"https://openalex.org/C71039073","wikidata":"https://www.wikidata.org/wiki/Q3439090","display_name":"Surface finish","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.352400004863739},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3424000144004822},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33059999346733093},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.31310001015663147},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.27129998803138733},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2678999900817871},{"id":"https://openalex.org/C2777879630","wikidata":"https://www.wikidata.org/wiki/Q2009662","display_name":"Surface finishing","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2572000026702881},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21872/annual2025_9071","doi":"https://doi.org/10.21872/annual2025_9071","is_oa":false,"landing_page_url":"https://doi.org/10.21872/annual2025_9071","pdf_url":null,"source":{"id":"https://openalex.org/S7407087832","display_name":"IISE Annual Conference & Expo","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IISE Annual Conference &amp; Expo 2025","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4378979139","https://openalex.org/W4396662295","https://openalex.org/W7222929541","https://openalex.org/W4409889283","https://openalex.org/W2074181469","https://openalex.org/W4321277385","https://openalex.org/W3211191198","https://openalex.org/W7140170431","https://openalex.org/W6908723760","https://openalex.org/W4317853070"],"abstract_inverted_index":{"The":[0,84],"surface":[1,14,22,31,78,101,141,163],"roughness":[2,23],"of":[3,92],"machined":[4,111],"parts":[5,110],"is":[6,25],"an":[7],"important":[8],"quality":[9,164],"indicator":[10],"because":[11],"it":[12],"affects":[13],"friction,":[15],"lubrication,":[16],"wear,":[17],"coating,":[18],"and":[19,33,45,57,90,124,154],"appearance.":[20],"Accurate":[21],"characterization":[24],"critical":[26],"for":[27,80,161],"achieving":[28],"the":[29,58,81,135],"desired":[30],"finish,":[32],"vision-based":[34,162],"models":[35],"have":[36],"shown":[37],"promise":[38],"by":[39],"surpassing":[40],"conventional":[41],"methods":[42],"in":[43,55],"speed":[44],"cost.":[46],"However,":[47],"insufficient":[48],"high-quality":[49,159],"training":[50],"data":[51,104],"limits":[52],"their":[53],"performance":[54],"accuracy":[56],"ability":[59],"to":[60,75,98,127,157],"generalize.":[61],"To":[62],"address":[63],"this":[64],"limitation,":[65],"we":[66],"propose":[67],"a":[68,113,152],"conditional":[69,85,136],"generative":[70],"adversarial":[71],"network":[72],"(GAN)":[73],"designed":[74],"generate":[76,139],"synthetic":[77,149],"images":[79,150],"turning":[82],"process.":[83],"GAN":[86,137],"takes":[87],"feed":[88],"rate":[89],"depth":[91],"cut":[93],"as":[94,146],"input":[95],"process":[96,144],"parameters":[97,145],"produce":[99,158],"turned":[100],"images.":[102],"Training":[103],"were":[105,118],"collected":[106],"from":[107],"1018":[108],"steel":[109],"with":[112],"HAAS":[114],"ST-15":[115],"Lathe.":[116],"Images":[117],"captured":[119],"under":[120],"varying":[121],"camera":[122],"angles":[123],"lighting":[125],"conditions":[126],"enhance":[128],"model":[129,165],"robustness.":[130],"Preliminary":[131],"results":[132],"show":[133],"that":[134],"can":[138],"detailed":[140],"patterns":[142],"given":[143],"input.":[147],"These":[148],"provide":[151],"scalable":[153],"cost-effective":[155],"solution":[156],"datasets":[160],"training.":[166]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-10-01T00:00:00"}
