Abstract: A system for examining a semiconductor specimen that includes a plurality of layers at respective different depths, and a plurality of holes. Each hole has a top portion at the surface of the specimen, and a bottom portion accommodated in one of the layers. The system includes a processing and memory circuitry (PMC) configured to provide an inspection image indicative of the holes, and process a hole image in the inspection image, without using a shape characterizing model. The processing includes segmenting the inspection image and determining data indicative of a contour of the top portion of the hole, and further segmenting the inspection image and determining data indicative of a contour of a shape enclosed within the contour of the top of the hole.

Abstract: There is provided an image generation system and method. The method comprises obtaining a runtime image of a semiconductor specimen with a low Signal-to-noise ratio (SNR), and processing the runtime image using a machine learning (ML) model to obtain an output image with a high SNR. The ML model is previously trained using a training set comprising a plurality of low SNR images associated with a high SNR image. The plurality of low SNR images correspond to a plurality of sequences of frames acquired in a plurality of runs of scanning a first site of the specimen. The high SNR image is generated based on the plurality of low SNR images. The training comprises, for each low SNR image: processing the low SNR image by the ML model to obtain predicted image data, and optimizing the ML model based on the predicted image data and the high SNR image.

Abstract: A method for fusion of radar and visual information, the method comprises: obtaining visual information and radar information about a three dimensional (3D) space located within a field of view of a camera that acquired the visual information and within a field of view of a radar that acquired the radar information; finding, based on the visual information, estimated visual-detection-based (VDB) objects and estimated VDB locations of the estimated VDB objects within the 3D space; wherein the estimated VDB locations exhibit a distance ambiguity; determining hybrid-detection-based (HDB) objects and HDB locations of the HDB objects, based on (i) the radar information, (ii) the estimated VDB objects, and (iii) the estimated VDB locations of the VDB objects.