Text feature extraction based on deep learning: a review
H Liang, X Sun, Y Sun, Y Gao - EURASIP journal on wireless …, 2017 - Springer
Selection of text feature item is a basic and important matter for text mining and information
retrieval. Traditional methods of feature extraction require handcrafted features. To hand …
retrieval. Traditional methods of feature extraction require handcrafted features. To hand …
A comprehensive review on critical issues and possible solutions of motor imagery based electroencephalography brain-computer interface
Motor imagery (MI) based brain–computer interface (BCI) aims to provide a means of
communication through the utilization of neural activity generated due to kinesthetic …
communication through the utilization of neural activity generated due to kinesthetic …
A CGRU multi-step wind speed forecasting model based on multi-label specific XGBoost feature selection and secondary decomposition
Z Jiang, J Che, M He, F Yuan - Renewable Energy, 2023 - Elsevier
Accurate wind speed forecasting is beneficial to reduce the risk of power system caused by
wind power uncertainty, which is of great significance for wind power grid connection …
wind power uncertainty, which is of great significance for wind power grid connection …
Passenger overall comfort in high-speed railway environments based on EEG: assessment and degradation mechanism
The overall comfort of train passenger is influenced by many environmental factors such as
vibration, noise and pressure. However, the couple effect of these influencing factors causes …
vibration, noise and pressure. However, the couple effect of these influencing factors causes …
Attention deficit hyperactivity disorder detection in children using multivariate empirical EEG decomposition approaches: A comprehensive analytical study
Early detection and timely therapeutic intervention are of prime importance to prevent the
severity of attention deficit hyperactivity disorder (ADHD) in children. Conventional …
severity of attention deficit hyperactivity disorder (ADHD) in children. Conventional …
VR motion sickness recognition by using EEG rhythm energy ratio based on wavelet packet transform
X Li, C Zhu, C Xu, J Zhu, Y Li, S Wu - Computer methods and programs in …, 2020 - Elsevier
Background and objectives Virtual reality motion sickness (VRMS) is one of the main factors
hindering the development of VR technology. At present, the VRMS recognition methods …
hindering the development of VR technology. At present, the VRMS recognition methods …
AHW-BGOA-DNN: A novel deep learning model for epileptic seizure detection
Abstract “Brain–Computer Interface”(BCI)—a real-life support system provides a way for
epileptic patients to improve their quality of life. In general, epileptic seizure detection using …
epileptic patients to improve their quality of life. In general, epileptic seizure detection using …
An efficient EEG based deceit identification test using wavelet packet transform and linear discriminant analysis
Background Brain–computer interface (BCI) is a combination of hardware and software that
provides a non-muscular channel to send various messages and commands to the outside …
provides a non-muscular channel to send various messages and commands to the outside …
Early classification of motor tasks using dynamic functional connectivity graphs from EEG
Objective. Classification of electroencephalography (EEG) signals with high accuracy using
short recording intervals has been a challenging problem in developing brain computer …
short recording intervals has been a challenging problem in developing brain computer …
Mlp with riemannian covariance for motor imagery based eeg analysis
P Yang, J Wang, H Zhao, R Li - IEEE Access, 2020 - ieeexplore.ieee.org
Stroke is one of the leading causes of disability and incidence. For the treatment of
prognosis of stroke patients, Motor imagery (MI) as a novel experimental paradigm, clinically …
prognosis of stroke patients, Motor imagery (MI) as a novel experimental paradigm, clinically …