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We propose a novel affinity matrix for image segmentation in this paper. The affinity matrix is constructed by using the Gaussian weighted Chi-square distance with neighborhood information, in which the vital spatial structure of the image is considered. An adaptive local scaling parameter is used to refine the segmentation rather than selecting a single scaling parameter. We demonstrate that graph-based...
In order to save energy of sensors in the process of gathering data and transmitting information, Compressive Sensing (CS), as a novel and effective signal transform technology, has been used gradually in Wireless Sensor Networks (WSNs). In traditional usages of CS techniques in the previous literatures, the sparsities of the signals has to be known beforehand, which is much more importance for their...
Distribution network optimization reconfiguration has important significance on improving distribution network operation. Ant colony algorithm is a common method in distribution network optimization reconfiguration. However, as there is the problem of slow convergence speed and local optimum, the development of ant colony algorithm is restricted in distribution network optimization. To solve the problems,...
The HITON_PC algorithm which is a state-of-the-art local causal discovery algorithm can deal with a dataset with a very small sample-to-variable ratio efficiently. But it cannot perform inefficiently on a dataset with a very large sample. To address this problem, a fast HITON_PC algorithm is presented which uses a new yet simple search strategy from high order to low order to improve the efficiency...
This paper presents a novel approach to achieve optimization for the audio features in compressed domain, which is the PSO (particle swarm optimization) algorithm basing on the attribute importance criterion of rough set theory. Our method firstly extracts the attributes of audio to form the feature vectors and pre-processes these vectors, then realizes the optimization using the proposed PSO algorithm,...
With the informationization of mechanical devices, high precision sensors have been widely applied to all kinds of mechanical devices for the information gathering. However, as the sensors are produced by various research centers and manufacturers, there is a considerable difficulty in examining and identifying the sensors. In this article, A new intelligent analysis model based on BP+GA algorithms...
Conventional image edge detection algorithms generate the information undetected and artificial information problems. In order to detect the image edge more effectively, an improved method based on grey model (GM) is brought forward. The neighborhood pixels of target pixel are selected to build the model. These data are preprocessed by translation transformation and logarithmic transformation. The...
Outlier detection can find its tremendous applications in areas such as intrusion detection, fraud detection, and image processing. Among many outlier detection algorithms, LOF is a very important density-based algorithm in which one critical step is to find the k-distance neighbors. In some privacy preserving circumstances, the cooperation between data holders is necessary while the privacy of the...
Motion vector prediction (MVP) is a high-efficiency technology for motion estimation in video compressing. In this paper, a novel MVP schedule strategy is proposed for AVS HD real-time encoder. A multi-stage MVP architecture is designed in this strategy for the macroblock (MB)-based pipelining. The tradeoff between complexity and performance is achieved for the MVP architecture which breaks the data...
In order to support more value-added services and a larger space for IP addresses, the Internet requries to classify IPv6 packets into flows for specific requirements. High performance IPv6 packet classification (PC) algorithms are therefore in high demand. This paper proposes a new IPv6 PC algorithm based on flow label (FL), called FLIN (Flow Label Initial Noticed). FLIN is fast and scalable with...
A novel layered object tracking algorithm for FLIR imagery is proposed based on mean shift algorithm and feature matching. First, infrared object is modeled by kernel histogram. Bhattacharyya coefficient is used to measure the similarity between object model and candidate model. The object is then localized by mean shift algorithm rapidly and efficiently. Because of the low contrast between infrared...
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