Tiago S. Nazaré

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Image classification is one of the main research problems in computer vision and machine learning. Since in most real-world image classification applications there is no control over how the images are captured, it is necessary to consider the possibility that these images might be affected by noise (e.g. sensor noise in a low-quality surveillance camera).(More)
In video data analysis of dynamic scenes, temporal characteristics of moving objects play an important role in decision-making. However, the temporal consistency of typical features used for video interpretation is low due to the overlap of the spectra of informative video signal component and the stochastic variations perturbing it. We propose a novel(More)
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