Deep learning and, in particular, convolutional neural networks (CNN) achieve very good
results on several computer vision applications like security and surveillance, where image
and video analysis are required. These networks are quite demanding in terms of
computation and memory and therefore are usually implemented in high-performance
computing platforms or devices. Running CNNs in embedded platforms or devices with low
computational and memory resources requires a careful optimization of system architectures …