Fourier transform based machine learning for defect examination of semiconductor specimens

Abstract

There is provided a system and method of defect examination on a semiconductor specimen. The method comprises obtaining an input image indicative of difference between an inspection image of the specimen and a corresponding reference image; and processing the input image using a trained machine learning (ML) system, to generate an output image representative of a defect map indicative of distribution of defect of interest (DOI) candidates in the input image. The ML system comprises a plurality of ML models operatively connected therebetween and previously trained together to perform defect detection on the input image based on Fourier transform. The output image is usable for further defect examination.