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The Data Driving Automated Vehicles:
Where It Comes From and Why Quality Matters

The diversity of environments in which autonomous vehicles must learn to operate is virtually endless: from unknown weather conditions, to pedestrians and cyclists, damaged roads, and other vehicles, machine learning models require vast amounts of data to account for as many scenarios as possible. But data quantity is not the only challenge. Accurately labeling that data is an even more challenging piece of the puzzle that data scientists and engineering teams are trying to solve.

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