Abstract: The present disclosure relates generally to systems, devices and/or processes for runtime linking of software component function implementations, and relates more particularly to linking particular function implementations based at least in part on a current execution environment.

Abstract: A method comprising the steps of obtaining image data captured at an image sensor using a focus configuration. A distance is determined for one or more objects in the image data, based on the focus configuration and a sharpness characteristic of the image data of the object. A depth map is then generated based on the determined distance.

Abstract: A computer-implemented method includes obtaining trained neural networks for performing a common task and test data for evaluating the performance of the trained neural networks, and inspecting the trained neural networks to identify functional blocks common to a plurality of the trained neural networks. For each identified functional block, extracting a respective network component for implementing the functional block within each of at least some of the trained neural networks, and for each extracted network component, evaluating performance of the network component, and storing performance data indicating said performance of the network component.

Abstract: Disclosed subject matter relates generally to forming a set of training parameters applicable to detection of two or more entities between and/or among a distribution of entities from a plurality of digitally stored observations.

Abstract: A computer-implemented method includes generating, using a scene generator, first candidate scene data; obtaining reference scene data corresponding to a predetermined reference scene; processing the first candidate scene data and the reference scene data, using a scene discriminator, to generate first discrimination data for estimating whether each of the first candidate scene data and the reference scene data corresponds to a predetermined reference scene; updating a set of parameter values for the scene discriminator using the first discrimination data; generating, using the scene generator, second candidate scene data; processing the second candidate scene data, using the scene discriminator with the updated set of parameter values for the scene discriminator, to generate second discrimination data for estimating whether the second candidate scene data corresponds to a predetermined reference scene; and updating a set of parameter values for the scene generator using the second discrimination data.

Abstract: A computer-implemented method includes generating, using a scene generator, first candidate scene data; obtaining reference scene data corresponding to a predetermined reference scene; processing the first candidate scene data and the reference scene data, using a scene discriminator, to generate first discrimination data for estimating whether each of the first candidate scene data and the reference scene data corresponds to a predetermined reference scene; updating a set of parameter values for the scene discriminator using the first discrimination data; generating, using the scene generator, second candidate scene data; processing the second candidate scene data, using the scene discriminator with the updated set of parameter values for the scene discriminator, to generate second discrimination data for estimating whether the second candidate scene data corresponds to a predetermined reference scene; and updating a set of parameter values for the scene generator using the second discrimination data.

Abstract: The present disclosure relates generally to Internet of Things (IoT)-type devices and, more particularly, to infrastructure for validating updates via a network of IoT-type devices.

Abstract: The present disclosure relates generally to Internet of Things (IoT)-type devices and, more particularly, to infrastructure for validating updates via a network of IoT-type devices.

Abstract: A method comprising the steps of obtaining image data captured at an image sensor using a focus configuration. A distance is determined for one or more objects in the image data, based on the focus configuration and a sharpness characteristic of the image data of the object. A depth map is then generated based on the determined distance.