Deep Learning Final Project: Built and trained Stacked CNN AutoEncoder and Deep CNN AutoEncoder based on STL-10 dataset - GitHub ... the process of convolution in keras using Theano. See details in ...

The framework employs a stacked sparse multi-layer CNN autoencoder to distil inputs into a robust feature set capturing complex temporal dependencies. These features are then processed by a CNN-BLSTM ...

The deep layer networks comprised of neurons are sometimes referred to as fully connected networks or fully connected layers, referencing the fact that a given neuron maintains a connection to all the ...

Deep learning has been applied in physical-layer communications systems in recent years and has demonstrated fascinating results that were comparable or even better than human expert systems. In this ...

Deep learning project for human activity recognition using time-series data from smartwatches and VICON motion capture systems. Includes 1D-CNN, LSTM, and autoencoder pretraining, with improved models ...