Implemented CV techniques with Deep Learning to interpret road scenarios, aiding perception of lane markings, obstacles, and traffic signs.
Utilized CNNs for feature extraction and pattern recognition, essential for decision-making.
Enhanced model accuracy and efficiency using gradient descent and fine-tuning method
The goal of this project is to train a neural network to drive a car in a simulator. The model learns from a dataset of images captured from a car's cameras and corresponding steering angles.