🔴 Project Title : Drowsiness Detection Using EEG Signals
🔴 Aim : To develop a deep learning model to detect drowsiness from EEG signals using various algorithms and compare their performance to identify the best-fitted algorithm based on accuracy scores.
🔴 Approach :
Exploratory Data Analysis (EDA):
Analyze and preprocess the EEG dataset.
Visualize EEG signals and class distributions.
Model Development:
Implement the provided deep learning model using TensorFlow and Keras.
Develop and implement three additional models:
Convolutional Neural Network (CNN).
Model Training and Evaluation:
Train each model on the EEG dataset.
Evaluate models using accuracy, precision, recall, and F1-score.
Compare performances to identify the best model.
Visualization and Conclusion:
Visualize training and validation metrics.
Provide insights and conclusions based on model comparisons.
abhisek247767
commented
13 hours ago
🔴 Project Title : Drowsiness Detection Using EEG Signals
🔴 Aim : To develop a deep learning model to detect drowsiness from EEG signals using various algorithms and compare their performance to identify the best-fitted algorithm based on accuracy scores.
🔴 Approach :
Exploratory Data Analysis (EDA):
Analyze and preprocess the EEG dataset. Visualize EEG signals and class distributions. Model Development:
Implement the provided deep learning model using TensorFlow and Keras. Develop and implement three additional models: Convolutional Neural Network (CNN). Model Training and Evaluation:
Train each model on the EEG dataset. Evaluate models using accuracy, precision, recall, and F1-score. Compare performances to identify the best model. Visualization and Conclusion:
Visualize training and validation metrics. Provide insights and conclusions based on model comparisons.
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