Perception Models for Self-Driving Cars with Jianxiong Xiao - TWiML Talk #58 episode artwork

EPISODE · Oct 25, 2017 · 41 MIN

Perception Models for Self-Driving Cars with Jianxiong Xiao - TWiML Talk #58

from The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) · host Sam Charrington

We are back with our second show this week, episode 2 of our Autonomous Vehicles Series. This time around we are joined by Jianxiong Xiao of AutoX, a company building computer vision centric solutions for autonomous vehicles. Jianxiong, a PhD graduate of MIT’s CSAIL Lab, joins me to discuss the different layers of the autonomous vehicle stack and the models for machine perception currently used in self-driving cars. If you’re new to the autonomous vehicles space I’m confident you’ll learn a ton, and even if you know the space in general, you’ll get a glimpse into why Jianxiong thinks AutoX’s direct perception approach is superior to end-to-end processing or mediated perception. The notes for this show can be found at twimlai.com/talk/58 For Series info, visit twimlai.com/av2017

Episode metadata supplied by the publisher feed · Published Oct 25, 2017

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Perception Models for Self-Driving Cars with Jianxiong Xiao - TWiML Talk #58

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