Linley Autonomous Hardware Conference 2017

Where: Hyatt Regency Hotel, Santa Clara, CA

When: April 6, 2017 

Linley Autonomous Hardware Conference 2017

Design innovations for self-driving automobiles are rapidly growing and becoming more sophisticated. Linley Autonomous Hardware Conference focuses on hardware design for autonomous vehicles and deep learning. System designers, chip designers, software designers, and OEM/ODMs are invited to attend and meet with industry leaders and network with peers.

See a Synopsys demo and hear multiple presentations to learn how to incorporate the necessary functionality into your automotive SoC faster and with significantly less risk.

Registration for the Linley Conference closes on April 3rd at 5:00pm.  

View complete agenda

Synopsys Demo

Deep Learning with DesignWare EV6x Vision Processor

Exhibits: 5:00 p.m. – 6:30 p.m.

Synopsys Presentations

Autonomous Driving with the MIPI Camera and Sensor Interfaces

Presenter: Hezi Saar, Staff Product Marketing Manager, Synopsys

Advanced Driver Assistance Systems (ADAS) SoCs for self-driving cars incorporate numerous interfaces for functions such as camera, radar, lidar and sensors. It is vital for such interfaces to meet the new stringent automotive standards, and offer the low power and high performance requirements that designers are looking for. The MIPI interfaces for camera (CSI-2) and sensors (I3C) are playing an essential role in enabling ADAS SoCs for autonomous driving. See how the MIPI specifications are implemented in automotive SoCs and why.


Deep Learning Requirements for Autonomous Vehicles

Presenters: Michael Thompson, Product Marketing Manager, Synopsys 

Deep-learning techniques for embedded vision are enabling cars to 'see' their surroundings and have become a critical component in the push toward fully autonomous vehicles. The early use of deep learning for object detection e.g., pedestrian detection and collision avoidance is evolving toward scene segmentation where every pixel of a high-resolution video stream must be identified. This presentation will discuss the current and next-generation requirements for ADAS vision applications, including the need for deep-learning accelerators.


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