Convolutional Neural Networks for Spherical Signal Processing via Spherical Haar Tight Framelets. (arXiv:2201.07890v1 [eess.SP])

In this paper, we develop a general theoretical framework for constructing
Haar-type tight framelets on any compact set with a hierarchical partition. In
particular, we construct a novel area-regular hierarchical partition on the
2-sphere and establish its corresponding spherical Haar tight framelets with
directionality. We conclude by evaluating and illustrating the effectiveness of
our area-regular spherical Haar tight framelets in several denoising
experiments. Furthermore, we propose a convolutional neural network (CNN) model
for spherical signal denoising which employs the fast …

arxiv convolutional neural networks networks neural networks processing signal