HGK18-405 – Accelerating Neural Networks for Vision Systems via FPGAs

Session ID: HGK18-405
Session Name: HGK18-405 – Accelerating Neural Networks for Vision Systems via FPGAs
Speaker: Glenn Steiner
Track: IoT, Embedded

★ Session Summary ★
The performance and accuracy of Convolutional Neural Networks for visual recognition has reached the point where researchers generally consider them to be more accurate than traditional algorithmic approaches. In this session we will examine implementation of a Binary Neural Network (BNN) on an FPGA with embedded processing system demonstrating four orders of magnitude greater performance than a software implementation on an embedded processor. We will start with the basic concepts of Convolutional Neural Networks. Next, we will examine why FPGAs with embedded processors provide the necessary flexibility to accommodate network precision as well as varying number of neurons and layers. Finally, we will demonstrate a BNN running on a 96 board doing real-time traffic recognition at over 8,000 images per second.
—————————————————
★ Resources ★
Event Page: http://connect.linaro.org/resource/hkg18/hgk18-405/
Presentation: http://connect.linaro.org.s3.amazonaws.com/hkg18/presentations/hgk18-405.pdf
Video: http://connect.linaro.org.s3.amazonaws.com/hkg18/videos/hgk18-405.mp4
—————————————————
★ Event Details ★
Linaro Connect Hong Kong 2018 (HKG18)
19-23 March 2018
Regal Airport Hotel Hong Kong

—————————————————
Keyword: IoT, Embedded
‘http://www.linaro.org’
‘http://connect.linaro.org’
—————————————————
Follow us on Social Media
https://www.facebook.com/LinaroOrg
https://www.youtube.com/user/linaroorg?sub_confirmation=1
https://www.linkedin.com/company/1026961