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Data Annotation For Autonomous Vehicle Development

Car makers, software companies and others spent more than $54 billion on autonomous vehicle development in 2019. Much of the near-term investment centers on the leap from partial driving automation to conditional driving automation where cars begin to actively see the world around them and begin to “think” for themselves. This progression happens when a system of onboard sensors and computers is trained using thousands of hours of video broken down into its component parts of different objects, analyzed, categorized, and then fed into algorithms.

Read the white paper to:

  • Understand the process of training autonomous vehicle algorithms
  • Differentiate between the types of data that go into self-driving cars and their complexity
  • Look into the Data Annotation Toolbox and learn more about its components
  • Learn how iMerit can power your autonomous vehicle deployment
Data annotation for autonomous vehicles
Autonomous vehicles complexity

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