Abstract: A first neural network generates a first output tensor based on an input tensor, the first output tensor comprising values to impart an effect to one or more features in the input tensor. A second neural network generates a second output tensor based on the input tensor, and the effect to be imparted to the one or more features is modulated, based at least in part, on the second output tensor.

Abstract: Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, in techniques to process image signal intensity values sampled from a multi color channel imaging device. In particular, such techniques may comprise application of convolution operations with kernel coefficients selected from a set of coefficient values such that the same coefficient value is to be applied to image signal intensity values of multiple pixel locations in an image frame.