paper

HexagDLy - Processing hexagonally sampled data with CNNs in PyTorch

arXiv:1903.01814 · doi:10.1016/j.softx.2019.02.010

Abstract

HexagDLy is a Python-library extending the PyTorch deep learning framework with convolution and pooling operations on hexagonal grids. It aims to ease the access to convolutional neural networks for applications that rely on hexagonally sampled data as, for example, commonly found in ground-based astroparticle physics experiments.

References in corpus (2)

HexagDLy - Processing hexagonally sampled data with CNNs in PyTorch · wovepaper