IEEE

Time-Series Classification Using a CNN-LSTM Model with Attention, Autoencoder, and K-Fold Cross-Validation

Abstract: Here, we propose a hybrid Deep Learning (DL) framework consisting of a Denoising Autoencoder (DAE), Convolutional Neural Network (CNN), Bidirectional LSTM (BiLSTM), and a custom Attention ...
IEEE

Optimizing Hybrid Classification Using 1D-CNN and LSTM for EEG-Based Emotion Recognition

Abstract: This research aims to enhance the ability of computers to classify emotional states from brain signals using EEG data. Emotions are complex mental states that can significantly affect a ...