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Electroencephalography (EEG) and brain-computer interfaces (BCI) are receiving increasing attention and expanding application in stroke study. To identify stroke patients and normal controls during mental rotation task, common spatial pattern (CSP) algorithm is employed to extract features from binary-class EEG which will be further to form the dictionary for sparse representation. In the classification...
In recent years, there are many great successes in using deep architectures for unsupervised feature learning from data, especially for images and speech. In this paper, we introduce recent advanced deep learning models to classify two emotional categories (positive and negative) from EEG data. We train a deep belief network (DBN) with differential entropy features extracted from multichannel EEG...
This paper begins with a discussion of the deficiency of current algorithms which use the number of the changing points of frame-difference as the threshold to determine a moving object. Based on human morphology, the feature of the human body in video surveillance is analyzed. Secondly, "the head and shoulder projection curve"," the proportion of head hair "and "height-width...
Classical edge detection method has great limitation, because the noise contained in the image has significant influence on the results, while the speed of edge detection and whether the edge can be detected or not are also the concerned problems. This paper proposed two edge detection methods based on the statistical features, which can accurately detect the edges and suppress the impact of the noise...
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