Deep Learning for Mobile

Takeaways

  1. Make sure the embedded system supports vectorized operations.
  2. Training framework doesn't matter. The difference in performance is often overshadowed by other latencies.
  3. Inference can often be optimized in many spots (image acquizition, RGB to float conversion, inference, etc.).
Challenges in Deep Learning for Mobile and Embedded.pdf