This was originally published in September 2019
In this paper we explore the use of AI to perform an image sorting task for a use case in NASCAR. Currently, the Richard Petty Motorsports (RPM) team acquires over 10,000 images per race and needs to sort them real-time to find the ones that contain the RPM car. This task is quite time consuming for an RPM team member, wasting valuable resources that could be deployed on more critical tasks. With AI, we can do this task quickly and with a low error rate. In addition to isolating just the RPM car, a large pool of cars can be detected and sorted accordingly. Starting with an unlabeled data set of thousands of images across several races, we trained and implemented a neural network to identify, classify and sort images with a high degree of accuracy.
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