20.500.12556/RUL-121554 Visual inspection system for anomaly detection on KTL coatings using variational autoencoders Electric cathode metal coating (KTL) is a popular choice for surface protection of metal components in the automotive industry. Due to the complex 3D shape of the parts and the glossy black color of the coating, machine vision inspection is very sensitive to variabilities among parts and to the variabilities in their positioning during the image acquisition. In this paper a variational autoencoder model for anomaly detection is presented to make further image processing more immune to variability and to detect coating defects more reliably. surface defect inspection imaging system anomaly detection deep generative models variational autoencoders KTL zaščita iskanje površinskih napak slikovni sistem detekcija anomalij globoki generativni model variacijski avtoenkoder true false true Angleški jezik Slovenski jezik Članek v reviji 2020-10-15 12:08:45 2020-10-15 12:08:48 2025-02-04 10:32:29 0000-00-00 00:00:00 2020 0 0 Str. 1558-1563 Vol. 93 2020 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.92:629.7(045) 2212-8271 10.1016/j.procir.2020.04.114 32754691 30177283 RAZ_Kozamernik_Nejc_2020.pdf RAZ_Kozamernik_Nejc_2020.pdf 1 2E1FADC582BB2C367EBACE42967FCA26 599827d4ed8d92ead2a2494ee1a6f3e5bea930c5b246928f5faf4944f5bbadc5 e9683506-a1ba-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=136496 https://www.sciencedirect.com/science/article/pii/S2212827120307496 1 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=136495 Fakulteta za strojništvo 0 0 0