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In the wireless sensor network (WSN), the operation reliability is usually evaluated by processing measured datas at network nodes. As the traditional algorithms exist the problems of the complex calculation and large energy consumption, a method for fault diagnosis of nodes in WSN based on rough set theory (RS) and support vector machine (SVM) is proposed in this paper. In this paper, we collect...
Traditional shadow suppression method based on HSV color space was proved to be an effective method. However, shadow detection with fixed parameters does not meet the change of monitored scene. According to vehicle property and scene change by the shadow projection, this article proposed an adaptive detection algorithm to achieve proposes of adaptive shadow suppression without adjusts the threshold...
For enhancing the accuracy and the versatility of automatic image classification, on the basis of the traditional Ant Colony Algorithm, we try to analysis the images from a new angle, and introduce the model of Ant Colony Algorithm, and take the exploratory research. According to the biological characteristic of the ant colony's community intelligence's, this method achieves the classification of...
In this paper, A picture is digitalized and the white noise is eliminated which appears in a motion picture of a videotape. The conventional method was developed for the purpose of repairing the blotch noise, focusing on the nature of violent video appear on the video noise, along with improvements to allow a better detection, that is, luminance threshold determination Used to improve interpolation...
To obtain the pose of a monocular camera installed on the robot relative to the static artificial landmarks in a prepared room is one of many good methods for indoor robot localization. However, the point correspondence problem caused by rotation of cameras and the point detection precision problem are not paid enough attention to. In this paper, we proposed a novel coplanar landmark and a method...
High accuracy for the classification of electroencephalogram (EEG) signal is an important basis for a brain-computer interface (BCI) system. In this paper, we proposed a novel approach to enhance the classification performance in identifying EEG signals, which classify EEG by combining multi-scale filters and principal component analysis (PCA). First, a multi-scale filter with different size of filter...
As we all know, GPS cannot totally meet the need of safety-of-life applications in civilian aviation especially the vertical accuracy and integrity. It is widely accepted that integrating GPS with barometric altimeter (Baro) can improve geometry and consequently provide performance enhancement especially in the vertical direction. This paper presents a novel data fusion algorithm of Baro and GPS based...
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