• A fast Logdet divergence based metric learning algorithm for large data sets classification 

      Mei, Jiangyuan; Hou, Jian; Chen, Jicheng; Karimi, Hamid Reza (Journal article; Peer reviewed, 2014)
      Large data sets classification is widely used in many industrial applications. It is a challenging task to classify large data sets efficiently, accurately, and robustly, as large data sets always contain numerous instances ...
    • A novel active contour model for unsupervised low-key image segmentation 

      Mei, Jiangyuan; Si, Yulin; Karimi, Hamid Reza; Gao, Huijun (Journal article; Peer reviewed, 2013)
      Unsupervised image segmentation is greatly useful in many vision-based applications. In this paper, we aim at the unsupervised low-key image segmentation. In low-key images, dark tone dominates the background, and gray ...
    • A novel data-driven fault diagnosis algorithm using multivariate dynamic time warping measure 

      Mei, Jiangyuan; Hou, Jian; Karimi, Hamid Reza; Huang, Jiarao (Journal article; Peer reviewed, 2014)
      Process monitoring and fault diagnosis (PM-FD) has been an active research field since it plays important roles in many industrial applications. In this paper, we present a novel data-driven fault diagnosis algorithm which ...
    • Metric learning method aided data-driven design of fault detection systems 

      Yan, Guoyang; Mei, Jiangyuan; Yin, Shen; Karimi, Hamid Reza (Journal article; Peer reviewed, 2014)
      Fault detection is fundamental to many industrial applications. With the development of system complexity, the number of sensors is increasing, which makes traditional fault detection methods lose efficiency. Metric learning ...