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

· 42 Minutes

PodcastThe TWIML AI Podcast

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

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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

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This story was published by The TWIML AI Podcast and written by Sam Charrington. SyncAI.news shows a preview; the complete article is on the publisher's site.

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