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Found 2 papers, 1 papers with code
Weight Equalizing Shift Scaler-Coupled Post-training Quantization
As a result, our proposed method achieved a top-1 accuracy of 69. 78% ~ 70. 96% in MobileNets and showed robust performance in varying network models and tasks, which is competitive to channel-wise quantization results.
SqueezeNext: Hardware-Aware Neural Network Design
One of the main barriers for deploying neural networks on embedded systems has been large memory and power consumption of existing neural networks.
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