When it comes to tackling leading-edge design challenges in fun ways, there’s no better place than DAC. For DAC 2018, we’ve created a System Design Contest targeting machine learning on embedded hardware.
If you think this is too leading edge for a design contest, you’d be mistaken: More than 100 teams registered for the contest. You can find a full list of the teams here: http://www.cse.cuhk.edu.hk/~byu/2018-DAC-HDC/teams.html
So how does the contest work:
Teams had the choice of using a Xilinx PynQ-Z1 FPGA-based development system or an NVIDIA Jetson TX2 development system, as well as software and deep-learning tools kits. Xilinx and NVIDIA donated boards to support the efforts.
Drone maker DJI donated a data-set that included more than 100 video clips with full annotation of the bounding box for the tracking object (a person or car).
The teams built either FPGA- or GPU-based systems to track people and vehicles from consumer drones using deep learning methods running on advanced embedded systems platforms. A hidden dataset is used to evaluate the performance of the designs in terms of accuracy and power consumption.
