A survey on methods and challenges in EEG based authentication
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 …
which are the results of synaptic activations of the brain's neurons. In recent years, it has …
Sign language translation using deep convolutional neural networks
Sign language is a natural, visually oriented and non-verbal communication channel
between people that facilitates communication through facial/bodily expressions, postures …
between people that facilitates communication through facial/bodily expressions, postures …
BWGAN-GP: An EEG data generation method for class imbalance problem in RSVP tasks
In the rapid serial visual presentation (RSVP) classification task, the data from the target and
non-target classes are incredibly imbalanced. These class imbalance problems (CIPs) can …
non-target classes are incredibly imbalanced. These class imbalance problems (CIPs) can …
Use of neural signals to evaluate the quality of generative adversarial network performance in facial image generation
There is a growing interest in using generative adversarial networks (GANs) to produce
image content that is indistinguishable from real images as judged by a typical person. A …
image content that is indistinguishable from real images as judged by a typical person. A …
A deep learning approach for brain computer interaction-motor execution EEG signal classification
Recently Noninvasive Electroencephalogram (EEG) systems are gaining much attention.
Brain-computer Interface (BCI) systems rely on EEG analysis to identify the mental state of …
Brain-computer Interface (BCI) systems rely on EEG analysis to identify the mental state of …
Multi-objective optimization approach for channel selection and cross-subject generalization in RSVP-based BCIs
Objective. Achieving high precision rapid serial visual presentation (RSVP) task often
requires many electrode channels to obtain more information. However, the more channels …
requires many electrode channels to obtain more information. However, the more channels …
Feature Extraction of EEG Signals for Seizure Detection Using Machine Learning Algorthims
MA Alsuwaiket - Engineering, Technology & Applied Science Research, 2022 - etasr.com
Epilepsy is a central nervous system disorder in which brain activity becomes abnormal and
causes periods of unusual behavior and sometimes loss of awareness. Epilepsy is a …
causes periods of unusual behavior and sometimes loss of awareness. Epilepsy is a …
SSVEP-assisted RSVP brain–computer interface paradigm for multi-target classification
Brain–computer Interface (BCI) is actively involved in optimizing the communication medium
between the human brain and external devices. Objective. Rapid serial visual presentation …
between the human brain and external devices. Objective. Rapid serial visual presentation …
The ensemble multi-scale convolution neural network for visual target detection EEG-based brain-computer interfaces
X Wang, M Dang, K Yang, X Cui, D Zhang… - … Signal Processing and …, 2024 - Elsevier
Human visual target detection based on electroencephalography (EEG) signals has been
widely used to categorize target and non-target images, especially visual event-related …
widely used to categorize target and non-target images, especially visual event-related …
Synthetic-Neuroscore: Using a neuro-AI interface for evaluating generative adversarial networks
Generative adversarial networks (GANs) are increasingly attracting attention in the computer
vision, natural language processing, speech synthesis and similar domains. Arguably the …
vision, natural language processing, speech synthesis and similar domains. Arguably the …