For detecting objects we will be using yolo v3 architecture. YOLO (You Only Look Once) is an object detection algorithm that can identify objects in an image and provide their locations, sizes, and classes in real-time. YOLO uses a single neural network to predict bounding boxes and class probabilities directly from full images in a single evaluation.
In a road segmentation problem, given an input image we have to identify where the roads are in that image. With the advent of deep learning we got rid of such hand crafting techniques wherein the computer will automatically learn the parameters given a diverse set of data. We will be using Fully Convolutional Networks (FCNs) for road segmentation.FCNs were one of the first techniques that introduced a method of segmentation end to end.
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