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Cheng Qian, Wei Yu, Chao Lu, David W. Griffith, Nada T. Golmie
Machine learning, as a viable way of conducting data analytics, has been successfully applied to a number of areas. Nonetheless, the lack of sufficient data is
Xing Liu, Wei Yu, Cheng Qian, David W. Griffith, Nada T. Golmie
The interconnection and digitization of the physical world has increased dramatically with the widespread deployment of network communication and the rapid
Fan Liang, Cheng Qian, Wei Yu, David W. Griffith, Nada T. Golmie
The advance of deep learning has shown great potential in applications (speech, image and video classification). In these applications, deep learning models are
Xing Liu, Wei Yu, Fan Liang, David Griffith, Nada T. Golmie
In this paper, we propose a general framework to adopt transfer learning in IIoT systems. Transfer learning is a machine learning technique that fully uses the
Xing Liu, Wei Yu, Fan Liang, David W. Griffith, Nada T. Golmie
Industrial Internet of Things (IIoT), also known as Industry 4.0, empowers manufacturing and production processes by leveraging automation and Internet of