Perception Models for Self-Driving Cars with Jianxiong Xiao - TWiML Talk #58
Published:Oct 25, 2017 19:43
•1 min read
•Practical AI
Analysis
This article summarizes a podcast episode featuring Jianxiong Xiao from AutoX, discussing perception models for self-driving cars. The focus is on the different layers of the autonomous vehicle stack and the machine perception models used. The article highlights AutoX's direct perception approach, contrasting it with end-to-end processing and mediated perception. The target audience seems to be those new to autonomous vehicles, but it also aims to provide insights for those already familiar with the field. The article serves as a brief introduction to the topic and a promotion for the podcast episode.
Key Takeaways
- •The episode discusses perception models in self-driving cars.
- •Jianxiong Xiao from AutoX is the guest.
- •The focus is on AutoX's direct perception approach.
Reference
“Jianxiong thinks AutoX’s direct perception approach is superior to end-to-end processing or mediated perception.”