Sai Prakash Challa

Abstract Machine vision and AI-based defect detection systems are increasingly deployed in manufacturing to support consistent product quality and high production efficiency. However, these automated inspection systems often suffer from sensitivity to imaging variability, dependence on large labeled datasets, and the need for manually engineered preprocessing pipelines–limitations that hinder accuracy and reliability in real industrial conditions.