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As better performance is achieved by deep convolutional network with more and more layers, the increasing number of weighting and bias parameters makes it only possible to be implemented on servers in cyber space but infeasible to be deployed in physical-world embedded systems because of huge storage and memory bandwidth requirements. In this paper, we proposed an efficient method to quantize the...