This is the implementation of the 50 layer Residual Neural Network architechture given the paper, Deep Residual Learning for Image Recognition by He et al. (https://arxiv.org/abs/1512.03385)
Trained the model with a GPU on the SIGNs dataset and achieved 99.81% training accuracy and 95.83% testing accuracy.
This is a considerable improvemement on the 78% testing accuracy achieved with a plain Neural Network. (https://github.com/sammyamajumdar/SignLanguage)
Author : Sammya Majumdar, 14th July 2020.