In recent years, machine learning algorithms, and more specifically deep learning
algorithms, have been widely used in many fields, including cyber security. However …

EEG is the recording of electrical activities of the brain, usually along the scalp surface,
which are the results of synaptic activations of the brain's neurons. In recent years, it has …

Deep learning has achieved excellent performance in a wide range of domains, especially
in speech recognition and computer vision. Relatively less work has been done for …

An increasing number of studies have been devoted to electroencephalogram (EEG) identity
recognition since EEG signals are not easily stolen. Most of the existing studies on EEG …

Discovering and exploiting shared, invariant neural activity in electroencephalogram (EEG)
based classification tasks is of significant interest for generalizability of decoding models …

Cognitive biometrics is an emerging branch of biometric technology. Recent research has
demonstrated great potential for using cognitive biometrics in versatile applications …

Affective brain-computer interface based on electroencephalography (EEG) is an important
branch in the field of affective computing. However, the individual differences in EEG …

Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has
become a potential field of research in recent years. Although several studies have been …

There is a growing need for sparse representational formats of human affective states that
can be utilized in scenarios with limited computational memory resources. We explore …

With the joint advancement in areas such as pervasive neural data sensing, neural
computing, neuromodulation and artificial intelligence, neural interface has become a …