Human Recognition Using Deep Neural Networks and Spatial Patterns of SSVEP Signals.Brain biometrics have received increasing attention from the scientific community due to their unique properties compared to traditional biometric methods.  In addition, with the help of deep neural networks, the spatial patterns are mapped into new (deep) representations where the discrimination between individuals is performed with a high correct recognition rate. 
Deep Neural Networks
Human Recognition Using Deep Neural Networks and Spatial Patterns of SSVEP Signals.Brain biometrics have received increasing attention from the scientific community due to their unique properties compared to traditional biometric methods.  In this study, we propose a novel approach by considering spatial patterns of the brain's responses due to visual stimulation at specific frequencies.  More specifically, we propose, for the identification of the individuals, to combine common spatial patterns with specialized deep-learning neural networks.  The adoption of common spatial patterns gives us the ability to design personalized spatial filters.  In addition, with the help of deep neural networks, the spatial patterns are mapped into new (deep) representations where the discrimination between individuals is performed with a high correct recognition rate. 
Spatial Patterns