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GitHub2y
Student Dropout Prediction using 1D CNN-LSTM with Variational Autoencoder Oversampling
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 ...
GitHub6y
1d-autoencoder · GitHub Topics · GitHub
sklearn keras classification autoencoder dimensionality-reduction eigenvectors apriori-algorithm cnn-autoencoders 1d-autoencoder. Updated Jun 19, 2019; Python; Improve this page Add a description, ...
IEEE2y
Wavelet Multiresolution Analysis Based Speech Emotion Recognition System Using 1D CNN LSTM Networks
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 ...
IEEE2y
Student Dropout Prediction using 1D CNN-LSTM with Variational Autoencoder Oversampling
Student Dropout Prediction using 1D CNN-LSTM with Variational Autoencoder Oversampling Abstract: Student dropout represents a social, resource and time loss for everyone involved. By identifying ...