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In order to cope with today's increasingly severe information security situations, trying to start develop the national information security literacy with students, information security education has been carried out in many countries around the world. Based on the clarification of the connotation of information security literacy, this paper conducted a survey of current situation of ISL education...
The Bayesian classifier model is a class of probability classifier based on the Bayesian theory. Compared with more sophisticated classification algorithms, such as decision tree and neural network, Bayesian classifier can offer very good classification accuracy in many practical applications. In this article, we perform a methodologically sound comparison of the seven methods, which shows large mutual...
Nearest Neighbor Classifier is one of the most classical lazy learning schemes. The basic nearest neighbor classifiers suffer from the common problem that the instances used to train the classifier are all stored indiscriminately, and as a result, the required memory storage is huge and response time becomes slow with a large database. In this paper, a new Instances Selection algorithm based on Classification...
This paper aims at automatically detection of car license plates via image processing techniques. The method used is a so-called gentle AdaBoost algorithm which is combined with a cascade structure. The gentle AdaBoost (GAB) algorithm is known to have a higher detection rate and a lower false positive rate than the basic discrete AdaBoost (DAB) which is currently reported being used for the license...
AdaBoost algorithm is an effective license plate detection method in the field of license plate recognition technology. A through analysis of three boosting algorithms (namely Discrete, Real and Gentle AdaBoost) is presented for license plate detection, including the algorithm details and experiment comparisons. The experimental results show the Gentle AdaBoost algorithm obtains an overall better...
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