Applies Gaussian smoothing using convolution to a randomly generated 1D array of data. The Gaussian smoothing is applied with both a kernel size of 3 and 6 ...

For a 2D kernel to be separable the rank of the matrix M must be 1. For a separable kernel the equation M = C * R holds. The method uses nonlinear least squares to minimize the residuals C * R - ...

Optical convolution kernel based on the volatile-modulation-compatible photonic memory: (a) Schematic architecture of a 4×4 OCK. The inset is the discrete device of OCK. (b) The nonvolatile multi ...

In computer vision, 2D convolution is arguably the most important operation performed by a ConvNet. Unsurprisingly, it has been the focus of intense software and hardware optimization and enjoys ...

Convolutional neural networks (CNNs) have found many applications in tasks involving two-dimensional (2D) data, such as image classification and image processing. Therefore, 2D convolution layers have ...