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Wensheng Chen, Yinxi Niu, Zhenhua Gan, Baoping Xiong and Shan Huang
Enhancing information representation in electromyography (EMG) signals is pivotal for interpreting human movement intentions. Traditional methods often concentrate on specific aspects of EMG signals, such as the time or frequency domains, while overlooki...
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Ruinan Chen, Jie Hu, Xinkai Zhong, Minchao Zhang and Linglei Zhu
Existing environment modeling approaches and trajectory planning approaches for intelligent vehicles are difficult to adapt to multiple scenarios, as scenarios are diverse and changeable, which may lead to potential risks. This work proposes a cognitive ...
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Jingjing Liu, Xinli Yang, Denghui Zhang, Ping Xu, Zhuolin Li and Fengjun Hu
Multi-node wind speed forecasting is greatly important for offshore wind power. It is a challenging task due to unknown complex spatial dependencies. Recently, graph neural networks (GNN) have been applied to wind forecasting because of their capability ...
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Huan Wang, Shi Qiu, Huping Ye and Xiaohan Liao
Plant growth is inevitably affected by diseases, and one effective method of disease detection is through the observation of leaf changes. To solve the problem of disease detection in complex backgrounds, where the distinction between plant diseases is h...
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Yohei Ueno, Taichi Tebakari, Keigo Noda and Kazuhiro Yoshimi
In this study, we examine the possibility of proactive floodwater diversion to fields via backwater in numerical experiments using multiple elevation data products with different spatial resolutions and explore the optimal timing of water diversion from ...
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