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For surveillance video, color information in scenes is important for detecting moving objects. This paper focuses on the selection of color space and the comparison of color distortion in codebook model which represents each background pixel with some codewords based on its color distortion and brightness bounds. Several computing methods are experimented for contrast. The results show that HSV color...
The end effects of Hilbert-Huang transform are produced in the Empirical Mode Decomposition(EMD) and the Hilbert transform for Intrinsic Mode Functions(IMF), which have a badly effect on Hilbert-Huang transform. In order to overcome this problem, the multi-objective allocation Genetic Algorithm (GA) to solve the kernel parameters selection of Least Squares Support Vector Machine (LSSVM)(GLHHT) is...
An improved BP neural network model was presented by modifying the learning algorithm of the traditional BP neural network, based on the Levenberg-Marquardt algorithm, and was applied to the breakout prediction system in the continuous casting process. The results showed that the accuracy rate of the model for the temperature pattern of sticking breakout was 96.43%, and the quote rate was 100%, that...
We propose a novel learning algorithm, called Bagging-Adaboost ensemble algorithm with genetic algorithm post optimization, for object detection that uses local shape-based feature. The feature is motivated by the scheme that use the chamfer distance as a shape comparison measure. It can be calculated very quickly using a look-up table. Random sampling boosting algorithm is used to select a discriminative...
We propose a novel learning algorithm, called Bagging-Adaboost ensemble algorithm with floating search algorithm post optimization, for object detection that uses local shape-based feature. The feature use the chamfer distance as a shape comparison measure. It can be calculated very quickly using a look-up table. Random sampling boosting algorithm is used to form an object detector. Floating search...
Polynomial pre-distortion techniques for power amplifier (PA) non-linearity based on indirect learning architecture (IDLA) are widely used. The benefit of the IDLA leaves unnecessary the assumption of a model for PA, corresponding parameters estimation and inverse construction. In this paper, a novel scheme based on IDLA for PA pre-distortion is proposed. It has better power spectral density (PSD)...
Knowledge reduction in decision table is important in both theory and application, and it outputs a minimal algorithm as a result. Set of the samples fitting the minimal algorithm is a concept over the set of all possible instances. But in unfamiliar environment, decision table is obtained randomly. So the obtained concept is an approximation to a potential target concept. We discuss the model of...
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