In this work, a transfer learning-based residual long short-term memory neural network with temporal pattern attention mechanism (TPA-ResLSTM) is proposed to realize real-time monitoring of wheel-rail force, even in scenarios where the dataset is deficient in sufficient features. Initially, a ...
connectivity data; (2) to conduct spatial convolution of functional time series based on the functional connections of brain regions characterized by the brain functional network; (3) to design functional connectivity based attention mechanism for understanding the discriminative power of each brain ...
Vision is dynamic, handling a continuously changing stream of input, yet most models of visual attention are static. Here, we develop a dynamic normalization model of visual temporal attention and constrain it with new psychophysical human data. We manip
Attention is an essential component of this process, its influence helping to impose the motor sampling pattern on the relevant sensory stream21,40. Accordingly, previous studies showed that overtly moving during an auditory attention task improves perceptual performance21,22. Importantly, these ...
1) the spatial-temporal attention mechanism 用来抓取动态的时序相关性,这是因为注意力机制可以获取nodes之间的动态相关性(dynamic correlation) (每个ST block里下面的蓝框) 2) the spatial-temporal convolution 利用图卷积神经网络抓取空间图案特征(spatial pattern)+ 标准卷积获取时序特征 (每个ST block里上面的蓝框...
Although the study of temporal attention takes its roots in the domains of perception and action, it is likely to be important across many cognitive domains (working memory, reinforcement learning and so on) and may contribute to a better understanding of many cognitive disorders. ...
Chao, Y.-W., et al.Rethinking the faster r-cnn architecture for temporal action localization. inProceedings of the IEEE conference on computer vision and pattern recognition. 2018. Chen, G., et al.,DCAN: Improving temporal action detection via dual context aggregation, inAAAI Conference on Art...
As mentioned previously, multivariate time series often entails a complex relationship pattern containing temporal and spatial relations in the real world. To address this problem, the DA-RNN is proposed to extract the spatial features using a CNN structure [17]. Shi et al. [43] employed convolu...
{Attention Mechanism Exploits Temporal Contexts: Real-Time 3D Human Pose Reconstruction}, author={Liu, Ruixu and Shen, Ju and Wang, He and Chen, Chen and Cheung, Sen-ching and Asari, Vijayan}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, ...
In contrast, others may produce a significant seasonality pattern, such as that shown in Case 3. With the temporal aspects of the network ignored, all three cases would produce similar prediction results even though they are entirely different. In our work, we focus our study on the graphs ...