A memory-based realization of a binarized deep convolutional neural network


A pre-trained deep convolutional neural network (CNN) is a feed-forward computation perspective, which is widely used for the embedded systems, requires high power-and-area efficiency. This paper realizes a binarized CNN which treats only binary 2-values (+1/−1) for the inputs and the weights. In this case, the multiplier is replaced with an EX-NOR circuit… (More)
DOI: 10.1109/FPT.2016.7929552


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