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

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

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)


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

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

ratings:
Length:
42 minutes
Released:
Oct 25, 2017
Format:
Podcast episode

Description

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
Released:
Oct 25, 2017
Format:
Podcast episode

Titles in the series (100)

This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders. These creators, builders, makers and influencers value TWiML as an authentic, trusted and insightful guide to all that’s interesting and important in the world of machine learning and AI. Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.