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In this paper, we propose a novel method to annotate the image of power grid objects (i.e., the electric equipment, the workers with different behaviors). This method is based on the convolutional neural networks (CNN). First, we obtain the attribute list of the image under the multi-label networks. Second, we employ the attribute-specific segmentation model to annotate the image. In this paper, we...
Aiming at the disadvantages of the single BP neural network in speech recognition, a method of speech recognition based on k-means clustering and neural network ensembles is presented in this paper. At first, a number of individual neural networks are trained, and then the k-means clustering algorithm is used to select a part of the trained individuals' weights and thresholds for improving diversity...
The Adaboosting has attracted attention for its efficient face-detection performance. However, in the training process, the large number of possible Haar-like features in a standard sub-window becomes time consuming, which makes specific environment feature adaptation extremely difficult. This letter presents a two-stage hybrid face detection scheme using Probability-based Face Mask Pre-Filtering...
In this paper, the Pixel-Based Hierarchical-Feature Adaboosting (PBHFA) method is presented. The purpose of this approach is the reduction of computation complexity in face-detection tasks. The Adaboosting method has attracted attention for its efficient face-detection performance. However, in the training process, the large number of possible Haar-like features in a standard sub-window becomes time...
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