Neuro-Inspired System Engineering - final project.
Tetiana Klymenko and Cristina Gil

ipynb notebooks (for training the models):

Full Model - performance of final model
Train FeedForwardNet - training feedforward Network
train_Linear_cGAN - training linear model of cGAN
NISE GanConv - training convolutional model for cGAN and evaluating KL divergence

Models (classes for models and Data Loader):
SignDataLoad.py - Dataloader for Sign Language MNIST data base (cannot be stored on github due to the memory limitations)
ganSigns.py - model for linear cGAN
ganConv.py - model for convolutional cGAN
TwoLayerNet.py - model for feedforward network
Solver.py - class to train the two-layer feedforward network
Hand_model.py - class to generate a model of the hand

Trained (contains .pth files with trained models)
discriminator_conv_short.pth - descriminator for convolutional cGAN pretrained on 6 classes.
generator_conv_short.pth - generator for convolutional cGAN pretrained on 6 classes.
twoLayer.pth - feedforward network for hand position classification (trained for variace 15).