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Undersampling is a widely adopted method to deal with imbalance pattern classification problems. Current methods mainly depend on either random resampling on the majority class or resampling at the decision boundary. Random-based undersampling fails to take into consideration informative samples in the data while resampling at the decision boundary is sensitive to class overlapping. Both techniques...
Visual surveillance is widely used in monitoring, entertainment and public security in recent years. This arouses the growing demand of automatic analysis system to deal with large amount of data produced by video cameras. Human action recognition is one of the most popular topics in video analysis. However, human activities are extremely complex and the dimensions of features extracted from a video...
Double compression is quite common due to image forgery and specific steganographic algorithms. It would notably impact results of steganalysis if not treated properly. This paper discusses the effects of double compression to steganalysis. Then, we evaluate the effect of double compression using L-GEM based RBFNN in comparison to widely adopted SVMs.
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