Energy Efficient Hardware Acceleration of Neural Networks with Power-of-Two Quantisation. (arXiv:2209.15257v1 [cs.CV])

Deep neural networks virtually dominate the domain of most modern vision
systems, providing high performance at a cost of increased computational
complexity.Since for those systems it is often required to operate both in
real-time and with minimal energy consumption (e.g., for wearable devices or
autonomous vehicles, edge Internet of Things (IoT), sensor networks), various
network optimisation techniques are used, e.g., quantisation, pruning, or
dedicated lightweight architectures. Due to the logarithmic distribution of
weights in neural network layers, a method providing …

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