Limited availability of labeled physiological data often prohibits the u...
Image restoration under adverse weather conditions has been of significa...
There is a growing need for sparse representational formats of human
aff...
Memory is a key component of biological neural systems that enables the
...
Electroencephalography (EEG) is shown to be a valuable data source for
e...
Deep learning based electroencephalography (EEG) signal processing metho...
Feature ranking and selection is a widely used approach in various
appli...
During daily activities, humans use their hands to grasp surrounding obj...
Recent promises of generative deep learning lately brought interest to i...
Human computer interaction (HCI) involves a multidisciplinary fusion of
...
Recent developments in biosignal processing have enabled users to exploi...
Recent developments in wearable sensors demonstrate promising results fo...
Across- and within-recording variabilities in electroencephalographic (E...
Objective: A variety of pattern analysis techniques for model training i...
Deep learning methods for person identification based on
electroencephal...
We introduce adversarial neural networks for representation learning as ...
It has been suggested that changes in physiological arousal precede
pote...
We present a novel hierarchical graphical model based context-aware hybr...
Causal terminology is often introduced in the interpretation of encoding...