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Majdi Sukkar, Madhu Shukla, Dinesh Kumar, Vassilis C. Gerogiannis, Andreas Kanavos and Biswaranjan Acharya
Effective collision risk reduction in autonomous vehicles relies on robust and straightforward pedestrian tracking. Challenges posed by occlusion and switching scenarios significantly impede the reliability of pedestrian tracking. In the current study, w...
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Ying-Qing Guo, Meng Li, Yang Yang, Zhao-Dong Xu and Wen-Han Xie
As a typical intelligent device, magnetorheological (MR) dampers have been widely applied in vibration control and mitigation. However, the inherent hysteresis characteristics of magnetic materials can cause significant time delays and fluctuations, affe...
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Wenhao Sun, Yidong Zou, Yunhe Wang, Boyi Xiao, Haichuan Zhang and Zhihuai Xiao
In the practical production environment, the complexity and variability of hydroelectric units often result in a need for more fault data, leading to inadequate accuracy in fault identification for data-driven intelligent diagnostic models. To address th...
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Yi Zhang, Hengchao Zhao, Zheng Zhang and Hongbo Wang
Addressing the automatic berthing task for vessels, this study introduces the Flow Matching Double Section Bezier Berth Method (FM-DSB) for handling downstream and upstream berthing instructions. By considering the orientation relationship between the di...
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Mingxin Zou, Yanqing Zhou, Xinhua Jiang, Julin Gao, Xiaofang Yu and Xuelei Ma
Field manual labor behavior recognition is an important task that applies deep learning algorithms to industrial equipment for capturing and analyzing people?s behavior during field labor. In this study, we propose a field manual labor behavior recogniti...
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