With the rise in popularity of Autonomous Driving technology, Computer Vision for Object Detection, and Deep Learning – The potential of AI has time and again proven to be colossal.
Although 2D camera data is used to teach autonomous vehicles to find their way from Point A to PointB, it comes with its own set of drawbacks.
Choosing an appropriate loss function is important as it affects the ability of the algorithm to produce optimum results as fast as possible.
The most important thing that the computer vision expert does is to decide which image annotation type is needed to build the most accurate model(s) for object detection.
State-of-the-Art Semantic Segmentation models need to be tuned in terms of memory consumption and fps output to be used in time-sensitive applications like autonomous vehicles. Here we study models like FCN, SegNets, ENets, and ICNets.