16-bit Precision of Convolutional Neural Networks on Microcontroller Units for 8-bit Costs
To deploy deep neural networks on edge hardware, highly efficient inference schemes are necessary that retain high accuracy. This work presents W16A16, a high precision (16-bit), fast speed, low energy quantization method. On a widely applied microcontroller architecture Armv7E-M, our proposed approach achieves faster...
Rui Liu, Benjamin Paassen
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