In order to solve the problem of low prediction accuracy when only vibration or oil signal is used to predict the remaining life of gear wear,a gear wear life feature fusion prediction method based on temporal pattern attention mechanism is proposed.Firstly,deep residual shrinkage network(DRSN)is...
Typical attention mechanism reviews the information at each previous time step and selects the relevant information to help generate the outputs, but it fails to capture the temporal patterns across multiple time steps. In this paper, we propose to use a set of filters to extract time-invariant...
the stateful LSTM module with an attention mechanism to learn the temporal order of the long-term sequences. The receptive field block efficiently increases the receptive field using dilated convolution layers and residual skip-connection, and it allows the model to learn spatiotemporal features from ...
Jones, M. R., Johnston, H. M. & Puente, J. Effects of auditory pattern structure on anticipatory and reactive attending.Cogn. Psychol.53, 59–96 (2006). PubMedGoogle Scholar Jones, M. R. Time, our lost dimension: toward a new theory of perception, attention, and memory.Psychol. Rev...
{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}, ...
The channels in the EEG signal represent the locations of the electrodes on the scalp, and the functional connectivity between different brain regions can be calculated by considering the dependencies among different channels. Similar to TTE, in STE we also used the attention mechanism to model the...
(2022). Mixformer: end-to-end tracking with iterative mixed attention. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 13,608–13,618). Piscataway: IEEE. MATH Google Scholar Xie, F., Wang, C., Wang, G., Cao, Y., Yang, W., & Zeng, ...
Trajectory Prediction Neural Network and Model Interpretation Based on Temporal Pattern Attention. Hongyu Hu (State Key Laboratory of Automotive Simulation and Control, Jilin University), Qi Wang, Ming Cheng, Zhenhai Gao. TITS 2023 [link] Traffic Prediction With Transfer Learning: A Mutual Information...
(ASTGCN) model, effectively capturing the daily periodicity, weekly periodicity, and nearest neighbors in traffic data. Convolution is used to capture the spatial pattern, and the output of these three components is weighted and fused by the attention mechanism module. The final prediction result ...
This is because of the temporal oscillation of the stimulus-driven attention that peaks at the focal moment. Results will be similar to the V-pattern of attentional changes around an attended location that are observed in the spatial domain. On the other hand, if the endogenous attention ...