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Intrusion detection is developed quickly because which has important position in network security. The method of SVM based on statistics learning theory is used in the intrusion detection system, which classifies detecting data efficiently, and achieves the aim that SVM can accurately predict the abnormal state of system. By the use of this method, the limitation of traditional machine learning method...
A fast subspace analysis and feature extraction algorithm is proposed which is based on fast Haar transform and integral vector. In rapid object detection and conventional binary subspace learning, Haar-like functions have been frequently used but true Haar functions are seldom employed. In this paper we have shown that true Haar functions can be successfully used to accelerate subspace analysis and...
A method of number-plate characters recognition using AdaBoost algorithm, which based on template matching is presented in order to improve recognition rate and reduce recognition time. The method is divided into two stages. In the first stage, classifier is trained by template matching which is improved through AdaBoost classification, at the same time, classification rules are found. Number-plate...
This paper presents a novel method for dimensionality reduction and for multi-class classification tasks. This method iteratively selects a series of simple but effective 1D subspaces, and then combines the corresponding 1D projections by Adaboost.M2. Its major advantages are: (1) it does not impose specific assumptions on data distribution; (2) it minimizes Bayes error estimation in low-dimensional...
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