Official implementation of our 2022 IEEE LA-CCI paper Student Dropout Prediction using 1D CNN-LSTM with Variational Autoencoder Oversampling by Eduarda C. Coppo, Rhuan S. Caetano, Leandro M. de Lima ...

A build-from-scratch 1D CNN language model used on patient's discharge summary phenotyping and comparing the LM with concept extraction based classification models. ... tensorflow gan autoencoder ...

The autoencoder is used to perform the dimensionality reduction of the wavelet features then the latent space is used to classify the emotions using the 1D CNN-LSTM model. We conducted a Monte-Carlo K ...

We propose a Wavelet based Deep Emotion Recognition (WaDER) method using an autoencoder and 1D convolutional neural network (CNN) and long short-term memory (LSTM) networks. The autoencoder is used to ...