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Efficient Processing of Deep Neural Networks: A Tutorial ...

Efficient Processing of Deep Neural Networks: A Tutorial and Survey This article provides a comprehensive Tutorial and survey coverage of the recent advances toward enabling Efficient Processing of deep Neural networks. B y V i v i e n n e S z e , S e n i o r M e m b e r I E E E , Y u -H s i n C h e n , S t u d e n t M e m b e r I E E E , Ti e n -J u Ya ng , Student Member IEEE, a n d J oe l S. E m e r , Fellow IEEE. ABSTRACT | Deep Neural networks (DNNs) are currently widely between various hardware architectures and platforms;. used for many artificial intelligence (AI) applications including be able to evaluate the utility of various DNN design computer vision, speech recognition, and robotics.

ral networks, which is the focus of this article.1 B. Neural Networks and DNNs Neural networks take their inspiration from the notion that a neuron’s computation involves a weighted sum of the input values. These weighted sums correspond to the value scaling performed by the synapses and the combining of those values in the neuron.

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