This example trains a Wide Residual Network on the SINS-10 dataset.
The Wide Residual Network family of architectures are described in the paper "Wide Residual Networks" by
Sergey Zagoruyko and Nikos Komodakis, published the 2016 British Machine Vision Conference.
The SINS-10 dataset is designed to enable practical significance testing for deep learning experiments. It can be
downloaded from https://www.cs.waikato.ac.nz/~ml/sins10/
This example trains a Wide Residual Network on the SINS-10 dataset.
The Wide Residual Network family of architectures are described in the paper "Wide Residual Networks" by Sergey Zagoruyko and Nikos Komodakis, published the 2016 British Machine Vision Conference.
The SINS-10 dataset is designed to enable practical significance testing for deep learning experiments. It can be downloaded from https://www.cs.waikato.ac.nz/~ml/sins10/