Autonomous Traffic Light Detection System (ATLDS)

In this project, I compared the performance of a TensorFlow multi-layer neural network (MLNN) and logistic regression by training both models on a dataset of traffic light images. The goal was to determine which model more accurately classified the images into different light states (red, yellow, green). By evaluating the models on metrics like accuracy, precision, and recall, I assessed their ability to handle the complexity of image data. The comparison highlights the strengths of neural networks in feature learning and logistic regression's performance on simpler, linear data.