Summary

This webinar will explore one of the hot topics in Automotive today, that of deep learning/convolutional neural network algorithms. We will look at the types of application they are used in, how they work and how the GPU Compute capability of PowerVR Graphics architecture enables vastly improved performance and power over traditional CPU execution. 

What you’ll learn

• How CNNs work
• How CNNs are advantageous in applications for semi and fully autonomous vehicles
• PowerVR compute architecture. How the structure lends itself to massively parallel computing

About the speaker

Bryce Johnstone, Director of Automotive Segment Marketing and 3rd Party Relations, Imagination Technologies

Bryce is a Director, responsible for promoting the company’s Ecosystem of third parties across all technologies including PowerVR, MIPS and ENSIGMA. This role involves identifying and engaging with key third parties to work with collaboratively on Imagination’s products as well as general outreach to the whole developer community. He has now added to his job portfolio as the Director for Automotive which encompasses working on relationships throughout the Automotive value chain including Tier 1s and Car manufacturer as well as key third parties to understand future requirements and what Imagination needs to deliver as IP into the rapidly changing car market over the coming years.

Paul Brasnett, Principle Research Engineer, Imagination Technologies

Paul is a principal research engineer leading a team responsible for imaging, image processing and computer vision algorithms within the PowerVR division of Imagination Technologies. Prior to this he was a senior research engineer at Mitsubishi Electric involved in image and video processing and participated in MPEG standardisation work. Paul has PhD and MEng degrees from the University of Bristol, UK.