Miroslav Avramov

Synthetic Data-Driven U-Net Semantic Segmentation for Automated Defect Detection

This study presents the development, training, and comparative evaluation of a U-Net-based convolutional neural network for pixel-level semantic segmentation of surface defects on structural components in nuclear reactor environments. Four defect classes are considered: cracks, corrosion, voids/pores, and background. D...