There is provided a system and method of semiconductor specimen examination. The method includes obtaining a plurality of images of a semiconductor specimen acquired by an examination tool; processing the plurality of images using a first machine learning (ML) model for defect detection, thereby obtaining, from the plurality of images, a set of images labeled with detected defects, wherein the first ML model is previously trained using a first training set comprising a subset of synthetic defective images each containing one or more synthetic defects, and a subset of nominal images; and training a second ML model using a second training set comprising at least part of the set of images labeled with detected defects, wherein the second ML model, upon being trained, is usable for defect detection with improved detection performance with respect to the first ML model.