This is a convolutional autoencoder neural network that is trained to classify 6 different human facial emotions:
The dataset that is used to train this model is the FER 2013 dataset.
The convolutional autoencoder is able to achieve 64% accuracy.
In comparison, the convolutional autoencoder accuracy is ~3% higher than a convolutional neural network.