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Session

What will next-gen sensor fusion and annotation look like for autonomous vehicles?

2 | Icebreaker

Sunday, December 08

08:00 PM - 10:00 PM

Live in Dearborn, Michigan

Less Details

  • How can sensor fusion and annotation systems be optimized for complex environments and weather conditions?
  • How can AI improve next-gen annotation and handle rare but critical driving scenarios?
  • What strategies can enhance data quality and labeling accuracy for training autonomous driving models?
Workshop

Speaker

Otto Debals

CEO & Co-Founder, Segments.ai

Otto is the CEO and co-founder at Segments.ai. He previously worked as an Associate at McKinsey & Company and holds a PhD in Mathematical Engineering from KU Leuven.

The Pop in Your Job – What drives you? Why do you love your job?
To help computer vision teams at robotics & AV/ADAS companies build better models through better data, focusing on 2D/3D and multi-sensor setups.

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Company

Segments.ai

https://segments.ai
Spend less time on labeling and more time building, running, and optimizing your ML algorithms. Segments.ai’s multi-sensor labeling platform lets you combine your 3D point cloud data and 2D image data in the same task to get the clearest picture possible. Upload your 3D data, then fuse information from multiple sensors to make annotating and categorizing your point clouds easier. Project and copy labels from 3D sensors to 2D sensors with advanced automation. You’ll get a faster and more consistent labeling workflow. The result: You get consistent labels across modalities and time, and you will have better, more accurate data to feed into your machine-learning algorithms. Your team will spend less time on quality checks and corrections.
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