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In this paper, we propose a novel framework for multi-objects tracking on solving two kind of challenges. One is how to discriminate different targets with similar appearance, the other is distinct the single target with serious variation over time. The proposed framework extracts discriminative appearance information of different objects from historical recordings of all tracked targets by a label...
Many studies have shown that Multiple Classifier Systems (MCSs) are more robust than single classifiers to evasion attacks for linear classifiers. However, to the best of our knowledge, the robustness of MCSs for non-linear classifiers has not been inves-tigated. This paper attempts to discuss two issues experimentally including a MCS is still more robust than a single classifier for non-linear classifiers,...
Identifying the major contributing factors to traffic collisions and their severity will assist highway safety improvement initiatives by improved facility design and educational program to address the needs due to the changes in demographics. The traffic collision data used in this study has been collected over the last 20 years on the rural highways and urban streets from Saskatchewan, Canada. In...
Support vector machine (SVM) is an algorithm based on structure risk minimizing principle and has high generalization ability, but sometimes we prefer to incremental learning algorithms to handle very vast data for training SVM is very costly in time and memory consumption or because the data available are obtained at different intervals. SVM works well for incremental learning model with impressive...
Using image classification approach for automatic image annotation is one promising method. In order to improve image annotation accuracy, recent researchers propose to use AdaBoost algorithm for the ensemble of classifiers. But in these researches, only fewer features are used. We construct multi-class classifiers for all the image low-level feature of multimedia content description interface and...
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