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This paper presents a novel approach for remaining useful life (RUL) prediction of rotating machinery using hierarchical deep neural networks (DNN). The different health stages are classified by a DNN-based health stage classifier trained by segmented degradation signal. This method builds several RUL predictors based on the health stages of the degradation process. Instead of modeling the entire...
This paper presents a novel approach for ball carrier detection and behavior recognition in a basketball match. Considering the cluttered background, fast motion of the players and the low resolution of the player images in the basketball match video, a covariance descriptor is adopted to fuse multiple visual features of the player, which can be characterized as a point on the Riemannian manifold...
Adaptive resonance theory (ART) architectures are important neural networks for unsupervised clustering. ART 2-A is one version of the ART family capable of clustering both binary and numeric data. However, real-world problems usually contain categorical data that cannot be processed by ART 2-A. A simple solution is using binary encoding to preprocess categorical data. Binary encoding is a simple...
Neural networks approach is an advanced methodology used for intrusion detection. As a type of neural network, Self-organizing Maps (SOM) is getting more attention in the field of intrusion detection. In this paper, some improvements on SOM algorithm are made in order to increase detection rate and improve the stability of intrusion detection, include: (1) Modify the strategy of ldquowinner-take-allrdquo...
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