Kymatio: Scattering Transforms in Python

Autor:	Andreux, Mathieu, Angles, Tomás, Exarchakis, Georgios, Leonarduzzi, Roberto, Rochette, Gaspar, Thiry, Louis, Zarka, John, Mallat, Stéphane, andén, Joakim, Belilovsky, Eugene, Bruna, Joan, Lostanlen, Vincent, Chaudhary, Muawiz, Hirn, Matthew J., Oyallon, Edouard, Zhang, Sixin, Cella, Carmine, Eickenberg, Michael
Rok vydání:	2018
Předmět:	Computer Science - Machine Learning Computer Science - Computer Vision and Pattern Recognition Computer Science - Sound Electrical Engineering and Systems Science - Audio and Speech Processing Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	The wavelet scattering transform is an invariant signal representation suitable for many signal processing and machine learning applications. We present the Kymatio software package, an easy-to-use, high-performance Python implementation of the scattering transform in 1D, 2D, and 3D that is compatible with modern deep learning frameworks. All transforms may be executed on a GPU (in addition to CPU), offering a considerable speed up over CPU implementations. The package also has a small memory footprint, resulting inefficient memory usage. The source code, documentation, and examples are available undera BSD license at https://www.kymat.io/
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1812.11214 Zobrazit plný text záznamu View this record from Arxiv