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Dual Precision Deep Neural Network

Published 2 Sep 2020 in cs.LG and cs.CV | (2009.02191v1)

Abstract: On-line Precision scalability of the deep neural networks(DNNs) is a critical feature to support accuracy and complexity trade-off during the DNN inference. In this paper, we propose dual-precision DNN that includes two different precision modes in a single model, thereby supporting an on-line precision switch without re-training. The proposed two-phase training process optimizes both low- and high-precision modes.

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