Abstract: Systems and methods are described herein for waveguide defect detection. In some examples, a statistical value of pixels of a number of image locations in one or more images of the waveguide can be computed. An extremity matrix can be generated based on an anomaly detector model and statistical pixel data that includes statistical values computed for respective image locations in the one or more images of the waveguide. A decision can be made to determine whether the waveguide is a conforming or a non-conforming waveguide based on the extremity matrix and a set of thresholds. In some examples, the statistical value is a mean intensity value or an average intensity value.

Abstract: Methods, systems, and/or devices for tuning the configuration settings of one or more RF apparatuses are provided. Various embodiments described herein regard a system that includes a radio frequency apparatus configured to operate based on a plurality of possible configuration settings to generate an output signal that is characterized by a performance metric. The system can also include a tuner that employs a machine learning engine having a training stage and an inference stage. The inference stage can be configured to, based on a machine learning model, search the possible configuration settings for a target configuration setting that results in the performance metric meeting defined bounds of an optimization threshold value.