Wei Li
Fudan University
2 Papers
Wei Li is an academic researcher from Fudan University. The author has contributed to research in topics: Deep learning & Artificial neural network. The author has an hindex of 2, co-authored 2 publications. Previous affiliations of Wei Li include University of York.
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Papers
EEG-Based Emotion Classification Using a Deep Neural Network and Sparse Autoencoder.
TL;DR: A novel deep neural network is proposed for emotion classification using EEG systems, which combines the Convolutional Neural Network, Sparse Autoencoder (SAE), and Deep Neural Network (DNN) together.
Alzheimer's disease detection using depthwise separable convolutional neural networks.
TL;DR: Wang et al. as discussed by the authors used the depthwise separable convolution (DSC) to replace the conventional convolution, which reduced the parameters and computational costs of the proposed neural network significantly compared with conventional neural networks.
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