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Convolutional neural networks(CNNs) have been widely applied in various applications. However, the computation-intensive convolutional layers and memory-intensive fully connected layers have brought many challenges to the implementation of CNN on embedded platforms. To overcome this problem, this work proposes a power-efficient accelerator for CNNs, and different methods are applied to optimize the...
The brain-actuated vehicle model is of great value to develop a brain-actuated assistive driving. Furthermore, this study helps to develop other BCI systems such as mobile robots, wheelchairs and unmanned aerial vehicle. In this paper, we propose a control model of motor-imagery based brain-actuated vehicle. This model includes a direction control and speed control combined driver model, a motor imagery...
Large-scale data is often represented as graphs in the field of modern cloud computing. Graph processing attracts more and more attentions when utilizing the cloud computing service. With the increasing attentions to process massive graphs (e.g., social networks, web graphs, transport networks, and bioinformatics), many state-of-the-art open source graph computing systems on a single node have been...
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