‘Deep Learning and Vision Algorithm Development in MATLAB Targeting Embedded GPUs’

The EMVA proudly announces that Mr. Alexander Schreiber, Principal Application Engineer at MathWorks, confirmed to share his expertise on Deep Learning at Embedded VISION Europe conference.

Alexander Schreiber joined the Application Engineering department of MathWorks Germany in 2008 and works as Principal Application Engineer and Technical Account Manager. He covers application areas of autonomous systems design, HW/SW co-design, automatic code generation and verification (HDL, C). Prior to joining MathWorks he worked as ASIC Library Designer, ASIC Designer and Project Manager for EDA and semiconductor companies. He holds a M.Sc. equivalent degree in Electrical Engineering from the University of Stuttgart.

Abstract of  Alexander’s presentation:

Learn how to adopt a MATLAB centric workflow to design, verify and deploy your computer vision and deep learning applications on to embedded Tegra-based platforms including Jetson TK1/TX1 and DrivePX boards. The workflow starts with algorithm design in MATLAB, which enjoys universal appeal among engineers and scientists because of its expressive power and ease-of-use. The algorithm may employ deep learning networks augmented with traditional computer vision techniques and can be tested and verified within MATLAB. Next, a compiler auto-generates portable and optimized CUDA code from the MATLAB algorithm, which is then cross-compiled and deployed to the Tegra board. The workflow affords on-board real-time prototyping and verification controlled through MATLAB. Examples of common computer vision algorithms and deep learning networks are used to describe this workflow, and their performance benchmarks are presented.

The debut of EMVA’s brandnew conference Embedded VISION Europe, supplemented by an already well booked table top exhibition, will take place 12-13 October 2017 in Stuttgart.

Find all conference details at www.embedded-vision-emva.org