Abstract: There is provided a system and method for examining a semiconductor specimen. The method includes obtaining a runtime image of the specimen, and providing the runtime image as an input to an end-to-end (E2E) learning model to process, thereby obtaining, as an output of the E2E learning model, runtime measurement data specific for a metrology application. The E2E learning model is previously trained for the metrology application using a training set comprising a plurality of training images of the specimen and respective ground truth measurement data associated therewith, and one or more cost functions specifically configured to evaluate, for the plurality of training images and corresponding training measurement data outputted by the E2E learning model, one or more metrology benchmarks from a group comprising precision, correlation, and matching.

Abstract: Systems, methods, and related technologies for device monitoring and device risk monitoring are described. In certain aspects, an indicator associated with a security risk is set based on communication between a first device having an associated elevated security risk and a second device. The indicator can be stored and may be used as a basis for performing a security action.

Abstract: Systems, methods, and related technologies for device monitoring and device risk monitoring are described. In certain aspects, an indicator associated with a security risk is set based on communication between a first device having an associated elevated security risk and a second device. The indicator can be stored and may be used as a basis for performing a security action.

Abstract: Systems, methods, and related technologies for device monitoring and device risk monitoring are described. In certain aspects, an indicator associated with a security risk is set based on communication between a first device having an associated elevated security risk and a second device. The indicator can be stored and may be used as a basis for performing a security action.