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In recent years, deep models offer a promising solution to extract powerful features. Motivated by the effectiveness of the Convolutional Networks (ConvNets) model in image classification and object detection, we present a visual tracking algorithm using the ConvNets model to extract multistage features. The key point of this paper is to show that the multi-stage features extracted by the ConvNets...
Motion detection is a fundamental and important part of many visual tracking systems and of other computer vision applications. In this paper, we present a robust and effective motion detection method for detecting foreground moving objects even with quick lighting changes and shadows in scenes. The proposed approach integrates YCbCr color features with texture by a fuzzy method based on Choquet integral...
In recent years, many studies show that kernel methods are computationally efficient, robust, and stable for pattern analysis. Many kernel-based classifiers were designed and applied to classify remote-sensed data, and some results show that kernel-based classifiers have satisfying performances. Many studies about hyperspectral image classification also show that nonparametric weighted feature extraction...
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