Method of deep learning-based examination of a semiconductor specimen and system thereof

Abstract

A computerized system and method of training a deep neural network (DNN) is provided. The DNN is trained in a first training cycle using a first training set including first training samples. Each first training sample includes at least one first training image synthetically generated based on design data. Upon receiving a user feedback with respect to the DNN trained using the first training set, a second training cycle is adjusted based on the user feedback by obtaining a second training set including augmented training samples. The DNN is re-trained using the second training set. The augmented training samples are obtained by augmenting at least part of the first training samples using defect-related synthetic data. The trained DNN is usable for examination of a semiconductor specimen.