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We propose a novel probabilistic framework that combines information acquired from different facial features for robust face recognition. The features used are the entire face, the edginess image of the face, and the eyes. In the training stage, individual feature spaces are constructed using Principle Component Analysis (PCA) and Fisher's Linear(More)
The Electroencephalogram (EEG) is a biological signal that represents the electrical activity of the brain and is the main resource of information for studying neurological disorders. Corruption of EEG signal is caused by occurrence of various artifacts like line interference, electroculogram, electrocardiogram and muscle activity [3]. These artifacts(More)
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