Searched for: +
(1 - 4 of 4)
document
Li, Wanda (author), Xu, Zhiwei (author), Sun, Yi (author), Gong, Qingyuan (author), Chen, Y. (author), Ding, Aaron Yi (author), Wang, Xin (author), Hui, Pan (author)
Outstanding users (OUs) denote the influential, 'core' or 'bridge' users in online social networks. How to accurately detect and rank them is an important problem for third-party online service providers and researchers. Conventional efforts, ranging from early graph-based algorithms to recent machine learning-based approaches, typically rely on...
journal article 2023
document
Ding, Chuanwei (author), Zhang, Li (author), Chen, Haoyu (author), Hong, Hong (author), Zhu, Xiaohua (author), Fioranelli, F. (author)
Radar-based solutions have attracted great attention in human activity recognition (HAR) for their advantages in accuracy, robustness, and privacy protection. The conventional approaches transform radar signals into feature maps and then directly process them as visual images. While effective, these image-based methods may not be the best...
journal article 2023
document
Chen, Junwen (author), Liu, Zhigang (author), Wang, H. (author), Nunez, Alfredo (author), Han, Zhiwei (author)
The excitation and vibration triggered by the long-term operation of railway vehicles inevitably result in defective states of catenary support devices. With the massive construction of high-speed electrified railways, automatic defect detection of diverse and plentiful fasteners on the catenary support device is of great significance for...
journal article 2018
document
Liu, C. (author), Cheng, Gang (author), Chen, Xihui (author), Pang, Y. (author)
Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was...
journal article 2018
Searched for: +
(1 - 4 of 4)