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Improving Applications of Systems of Systems using Ultra Fast Instance Segmentation

Computer Vision is a valuable tool that can be used to enhance the components of many working systems. In particular, many applications can be improved by incorporating instance segmentation into their designs to help better process visual information in the surrounding environment. However, instance segmentation algorithms have traditionally been too slow to be used by any real-time systems that could benefit from using them. This includes examples such as self-driving vehicles or autonomous drones. In this work we provide an overview of the shortcomings for current instance segmentation algorithms, introduce an ongoing effort to create a new one that achieves ultrafast speeds without sacrificing competitive accuracy, and explain the advantages of employing an ultra-fast real-time version of one as a component in different systems.