SoC Prototyping of AI-Based Vision Applications
Deep learning has become a popular technique for video and image processing applications such as classification and object detection. System-on-chip (SoC) devices are often used for edge-based applications, but deep learning networks are challenging to implement on FPGA hardware. Learn how to explore, simulate, and deploy SoC implementations of a vision processing application that uses deep learning, from within MATLAB.
- Partitioning pre-processing, deep learning inference, and post-processing functionality to SoC components
- Pre-processing the incoming video stream on FPGA hardware
- Configuring and deploying the deep learning processor FPGA IP
- Simulating and adjusting the system components
- Deployment to a Xilinx® Zynq® Ultrascale+(TM) MPSoC ZCU102 board
Target industries: AeroDef, Auto, IA&M