We get creative with an effects chain inspired by Jon Hopkins, and a heavy dose of felt piano ...

Abstract: Deep learning is a powerful technique for image processing. Convolution neural network (CNN) is one of the widely used approaches for hyperspectral image (HSI) classification. These methods ...

You can use these live scripts as demonstrations in lectures, class activities, or interactive assignments outside class. This module covers the definition and computation of 1D and 2D convolution, as ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

Abstract: A new approach to an analog ultra-low power medium-resolution vision chip design is presented. The prototype chip performs low-level image processing algorithms in real time. Only a ...

A team of researchers from the Institute for Basic Science, Yonsei University, and the Max Planck Institute have developed a new artificial intelligence (AI) technique that brings machine vision ...

A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...

This package wraps the core functionality of libvips image processing library by exposing all image operations on first-class types in Go. Libvips is generally 4-8x faster than other graphics ...

Hyperspectral images are a valuable tool for remotely sensing important characteristics of a variety of landscapes, including water quality and the status of marine disasters. However, hyperspectral ...