Abstract
Despite the Deep Neural Network (DNN) has achieved a great success in image recognition, the resource needed by DNN applications is still too much in terms of both memory usage and computing time, which makes it barely possible to deploy a whole DNN system on resource-limited devices such as smartphones and small embedded systems. In this paper, we present a DNN model named EffectFace designed for higher storage and computation efficiency without compromising the accuracy.
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