Deep Learning in Simulink for Intel ARM CPUs:Generate C++ Code Using Simulink Coder & Embedded Coder

Learn how you can use Simulink® to design complex systems that include decision logic, controllers, sensor fusion, vehicle dynamics, and 3D visualization components.

As of Release 2020b, you can incorporate deep learning networks into your Simulink models to perform system-level simulation and deployment.

Learn how to run simulations of a lane and vehicle detector using deep learning networks based on YOLO v2 in Simulink on ARM® Cortex®-A and Intel® CPUs. The Simulink model includes preprocessing and postprocessing components that perform operations such as resizing incoming videos, detecting coordinates, and drawing bounding boxes around detected vehicles. With the same Simulink model, you can generate optimized C++ code using ARM Compute Library or Intel MKL-DNN (oneDNN) to target ARM Cortex-A and Intel CPUs.

Additional Resources:

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[liurui]

The content and the topic does not match. Shouldn't you check "Generate GPU Code" to generate GPU code in the config set?