Electroencephalogram (EEG)-based emotion computing has become a hot topic of brain-
computer fusion. EEG signals have inherent temporal and spatial characteristics. However …

Electroencephalogram (EEG) signals contain complex useful information about brain
activities. These EEG signals are noisy, highly varying and nonstationary in nature. Hence …

The sleep loss (SL) are one of the important diseases that endanger the health of aging
individuals. This study evaluated SL in aging individuals, and explored the relationship …

Recently, electroencephalogram (EEG) emotion analysis has attracted increasing attention
in many fields, such as neuroscience and brain-computer fusion. Due to the spatial channel …

Emotions significantly impact human thinking, judgment, health, and communication. EEG-
based emotion detection has advanced with the use of Brain-Computer Interface (BCI) …

The major aim of this paper is to explain the data poisoning attacks using label-flip**
during the training stage of the electroencephalogram (EEG) signal-based human emotion …

Recognition of emotions from multi-modal physiological signals is one among the toughest
tasks prevailing amid the research communities. Most existing works have focused on …

Existing deep learning models suffer from out-of-distribution (ood) performance drop in
computer vision tasks. In comparison, humans have a remarkable ability to interpret images …

Emotion detection is a method which can be used to determine publics' attitudes, feelings,
and feelings towards a specific target, such as persons, groups, organizations, various …

Emotions have a significant effect on daily living and they are linked to physical as well as
mental wellness. People use words, noises, body language and facial expressions to …