Object Detection using YOLO model
In this project, a real-time object detection application is created for the self-driving car using YOLO model. Given images taken from the car-mounted camera, the program outputs a list of bounding boxes indicating not only the position and size of objects but also the class of objects. In particular, a Deep CNN is used to convert the preprocessed image to an encoding, from which the bounding boxes with high probability is computed by non-max suppression.