To assist clinical diagnosis, an EEG-based deep learning frame, which is named the gated temporal-separable attention network (GTSAN), is proposed in this paper for depression recognition. GTSAN model extracts discriminative information from EEG recordings in two ways. On the one hand, the gated...
gated temporal convolutional networkglobal attention mechanismnearest neighboringAs the core technique of the prognostic and health management field, data-driven remaining useful life (RUL) prediction generally requires abundant data to construct reliable mappings from monitoring data to machines' RUL labels....
标题论文标题:Spatiotemporal Adaptive Gated Graph Convolution Network for Urban Traffic Flow Forecasting 摘要 城市交通流预测是智能交通系统中的一个关键问题。由于动态城市交通条件所带来的复杂的时空依赖性和本质的不确定性,这是一个相当具有挑战性的问题。在现有的大多数方法中,基于局部空间邻近性,利用图神经网络(...
与LSTM的区别GRU就是我们模型中的门值,这个值得来的是从注意于学习突出表现的注意模块每个时间步骤所获得的。 3. Temporal Attention-Gated Model 给定一个可能的未分段序列作为输入嘈杂信息的观察,我们的目的是:(1)我们的输入序列中的每个时间步观察得分并计算显着性,以及(2)构建一个最适合于序列分类任务的隐藏表...
2.2. Spatiotemporal Attention Mechanism Graph convolutional neural network can capture the local spatial correlation between adjacent nodes in graph, but different adjacent points have different impact on the current node. The key idea of spatial attention mechanism is to pay adaptive attention to the ...
Temporal convolution neural network ENN: Elman neural network ANFIS: Artificial neural fuzzy inference system ELM: Extreme learning machine CLSTM: Convolution long short-term memory PCC: Pearson's correlation coefficient References Oral B, Tuncar EA (2024) A review of short-term wind power...
Recently channel attention mechanism playing a major role in improving the performance of deep convolution neural networks. Even though there is an improvement in the performance, but there is an increase in complexity of the model network. It is difficult for CNN alone to correctly model the ...
Furthermore, our study reveals that a novel, sparsely used, architecture which integrates Recurrent Highway Networks with neural gating and attention mechanisms, emerges as the best performing architecture in high-dimensional spatiotemporal forecasting of dynamical systems. ...
As such,to explore the temporal context in utterances, different Recurrent Neural Network (RNN) architectures such as LSTMs, GRU’s etc are widely explored in SER domain [26], [27]. Moreover, to exploit the usefulness of both CNNs and RNNs, combined CNN+LSTM architectures is now a ...
We propose a new channel-fused gated temporal convolutional network. First, a channel fusion and gating mechanism is designed to improve temporal convolutional networks, allowing the model to obtain higher-level features. Second, we improve the channel fusion module by the short-term average energy ...