Shaohua Wang

Processed ECG signals to determine if a patient's heart rate is normal.

Implemented noise reduction techniques to improve signal quality.

Experimented with various machine learning models to achieve the best prediction accuracy.

Utilized a camera to capture various road images.

Implemented a ResNet (Residual Network) model to train a custom deep learning algorithm.

Applied the trained model to control an vehicle, enabling it to navigate the road based on real-time situation recognition.

Leveraged OpenAI Gym environment to develop and test a reinforcement learning model.

Implemented the algorithm from "Human-level control through deep reinforcement learning" to create a Q-learning model.