Case Study
Monday, June 19
06:00 PM - 06:30 PM
Live in Berlin
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The further advancement of autonomous driving, which strongly relies on machine learning based perception systems, requires rethinking the communication between the vehicle and the user. Combining information from the environment perception with in-cabin monitoring and especially the perception of the driver’s reactions brings together important aspects in autonomous vehicles. Departing from different perception models and comparing models for detecting bodies outside the vehicle with far more detailed models for in-cabin detection, the presentation will discuss how external perception systems communicate with the user and what improvements should be achieved in the future in autonomous vehicles. In this session you will learn more about
Shubham Shrivastava works as Technical Expert and Lead, 3D Perception at Ford. He is leading a team of talented machine learning and robotics engineers towards building vision-centric 3D perception solutions at Ford Autonomy. His work includes building an end-to-end 3D Perception stack for Ford L2+ vehicles on the road, and the development of a flexible and scalable machine-learning framework for all ML tasks within Ford.