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Failing to learn: Autonomously identifying perception failures for self-driving cars

University of Michigan, July 26, 2018

One of the major open challenges in self-driving cars is the ability to detect cars and pedestrians to safely navigate in the world. Deep learning-based object detector approaches have enabled great advances in using camera imagery to detect and classify objects. But for a safety critical application such as autonomous driving, the error rates of the current state-ofthe-art are still too high to enable safe operation.

https://arxiv.org/pdf/1707.00051.pdf

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