Hole Detection

Hole detection encompasses diverse applications, from identifying missing data in 3D models and images to improving the efficiency of robotic drilling operations. Current research focuses on developing robust algorithms, including those based on reinforcement learning for robotic control and transformer networks for image inpainting, that can accurately locate holes even in complex or noisy data, such as those containing singular vertices or large missing regions. These advancements are crucial for improving the accuracy and efficiency of various processes across diverse fields, from computer-aided design to autonomous robotics and machine learning.