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Task-based functional magnetic resonance imaging (tfMRI) is widely used to localize brain regions or networks in response to various cognitive tasks. However, given two groups of tfMRI data acquired under distinct task paradigms, it is not clear whether there exist intrinsic inter-group differences in signal composition patterns, and if so, whether these differences could be used for data discrimination...
Sparse coding has been increasingly used to explore brain networks using functional magnetic resonance imaging (fMRI). However, modeling and comparing brain network based on sparse coding is still challenging, especially in clinical applications. In this study, we propose a novel temporal sparse coding method to identify functional connectivity biomarkers in patients with Attention-Deficit/Hyperactivity...
In this paper, we present a novel human detection method by devising a saliency framework on visual attention HOG features for infrared thermal imaging cameras. The proposed approach extends the saliency map by including the representation not only spatial features but also gaze distribution features. During thermal videos, the developed framework consists several computational stages: (a) the regions...
Skin segmentation is the cornerstone of many applications such as gesture recognition, face detection, and objectionable image filtering. In this paper, we attempt to address the skin segmentation problem for gesture recognition. Initially, given a gesture video sequence, a generic skin model is applied to the first couple of frames to automatically collect the training data. Then, an SVM classifier...
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