functions that yield fairly good results—sufficient that a generated image visually appears random. 1D, 2D, and 3D versions are included, again referring to the number of inputs to generate a ...

1. The input consists of a large set of scattering images with intensities I acquired on a 2D liquid, meaning that each exposure is taken on a random ensemble of multiple identical particles.

To that end, they train a generative model for 3D shapes such that rendering the shapes generates images matching the distribution of a 2D data set. The generator model takes in a random input ...

Researchers propose a True Random Number Generation (TRNG) using dark pixel values of images received from the CMOS image sensor to provide unpredictability to the passwords. “Random Number Generators ...