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Xiaojiao Gu, Yang Tian, Chi Li, Yonghe Wei and Dashuai Li
The fault diagnosis method proposed in this paper can be applied to the diagnosis of bearings in machine tool spindle systems.
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Ting Guo, Nurmemet Yolwas and Wushour Slamu
Recently, the performance of end-to-end speech recognition has been further improved based on the proposed Conformer framework, which has also been widely used in the field of speech recognition. However, the Conformer model is mostly applied to very wid...
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Gaoyuan Cai, Juhu Li, Xuanxin Liu, Zhibo Chen and Haiyan Zhang
Recently, the deep neural network (DNN) has become one of the most advanced and powerful methods used in classification tasks. However, the cost of DNN models is sometimes considerable due to the huge sets of parameters. Therefore, it is necessary to com...
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Zhuo Li, Hengyi Li and Lin Meng
Currently, with the rapid development of deep learning, deep neural networks (DNNs) have been widely applied in various computer vision tasks. However, in the pursuit of performance, advanced DNN models have become more complex, which has led to a large ...
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Siriwan Intawichai and Saifon Chaturantabut
An accelerated least-squares approach is introduced in this work by incorporating a greedy point selection method with randomized singular value decomposition (rSVD) to reduce the computational complexity of missing data reconstruction. The rSVD is used ...
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Zhiyang He, Weidong Cheng, Jiqiang Xia, Weigang Wen and Meng Li
With the development of industrial robots and other mechanical equipment to a higher degree of automation, mechanical systems have become increasingly complex. This represents a huge challenge for condition monitoring. The separation of vibration source ...
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Chao Zhou and Tao Zhang
In real applications, massive data with graph structures are often incomplete due to various restrictions. Therefore, graph data imputation algorithms have been widely used in the fields of social networks, sensor networks, and MRI to solve the graph dat...
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Bo-Lin Jian, Wen-Lin Chu, Yu-Chung Li and Her-Terng Yau
This study proposed the concept of sparse and low-rank matrix decomposition to address the need for aviator?s night vision goggles (NVG) automated inspection processes when inspecting equipment availability. First, the automation requirements include mac...
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Zhangren Tu, Huiting Liu, Jiaying Zhan and Di Guo
Multidimensional nuclear magnetic resonance (NMR) spectroscopy is one of the most crucial detection tools for molecular structure analysis and has been widely used in biomedicine and chemistry. However, the development of NMR spectroscopy is hampered by ...
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Junxiu Zhou, Yangyang Tao and Xian Liu
The fundamental challenge of salient object detection is to find the decision boundary that separates the salient object from the background. Low-rank recovery models address this challenge by decomposing an image or image feature-based matrix into a low...
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