AnExtremelyEfficientConvolutionalNeuralNetworkforMobileDevices
Abstract We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e.g., 10-150 MFLOPs). The new architecture utilizes two new operations, pointwise group convolution and channel shuf- fle, to
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