AutoSens is a world class conference addressing the future of self-driving vehicles
AutoSens gets right to the heart of the challenges facing vision system engineers of today and tomorrow.
Open Minds to Open Standards for the Deep Learning Automotive Solutions
Thursday, September 19, 11:35am to noon | Minerva Seminar Room Presented by Stephane Strahm of Kalray
Overview: In order to temper the automotive industry’s rapidly advancing connected technology, standards are being evaluated or created to improve interoperability of components as system complexity grows. This is happening nowhere more so than in the area of intelligent data compute for tactical driving systems – autonomous vehicles. Khronos’ open standards are a key solution to providing versatility in the supply chain and embracing more of the collective AI development community to solve tomorrow’s goals. This presentation will take you through the success of Khronos open standards for machine learning, embedded vision and heterogeneous compute and show you how you can participate to shape the future of safety-critical APIs required for autonomous software solutions.
Safety critical open standards opens up interoperability possibilities
Allow for versatility in your supply chain
Khronos open standards give you a say in defining the API features specification
Influence a specification that is compatible with your competitor’s supplier product
Spread the intellectual work load across suppliers with a common interface
Increase the adoption of your products by using Open Standards
Get an overview and understanding of the deep learning compute stacks used in automotive and the open standards available from Khronos for vendors.
Khronos can provide a platform to develop new open standard safety critical APIs
Help define compatibility and open up innovation using open standards
Other Themes to be addressed at AutoSens 2019
Developments in sensor technologies, including camera monitoring systems, LIDAR, radar, and time-of-flight imaging
Functional safety and testing, including real world versus virtual validation
Driver and compartment monitoring on the way towards autonomous vehicles
Image quality and standardization
How to improve the performance and safety of automated vehicles
Image and signal processing requirements
How computer vision affects camera design and SOC design
Incorporating AI and deep learning into embedded systems
Regulation/ethics considerations for self-driving vehicles
Human factors in sensor and autonomous vehicle design
Mapping and localization for driverless vehicles
Can We Have Both Safety and Performance in AI for Autonomous Vehicles?
Thursday, September 19, 12 noon | Minerva Seminar Room Presented by Andrew Richards, Codeplay
An introduction on implementing AI on appropriate processor architectures
The issues in making AI safe enough for automotive autonomous systems
The relevant standards and how to achieve both safety + performance with them
Thursday, September 19, 12:25 noon | Minerva Seminar Room Presented by Illya Rudkin, Principal Software Engineer, Codeplay Software