Deep learning for motor imagery EEG-based classification: A review
Objectives The availability of large and varied Electroencephalogram (EEG) datasets,
rapidly advances and inventions in deep learning techniques, and highly powerful and …
rapidly advances and inventions in deep learning techniques, and highly powerful and …
Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
DNA microarray technology is the fabrication of a single chip to contain a thousand genetic
codes. Each microarray experiment can analyze many thousands of genes in parallel. The …
codes. Each microarray experiment can analyze many thousands of genes in parallel. The …
An overview of brain fingerprint identification based on various neuroimaging technologies
S Zhang, W Yang, H Mou, Z Pei, F Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As a novel category of biometric features, research on brain fingerprints has become a hot
topic in neuroscience, not only for its reliable performance on individual identification but …
topic in neuroscience, not only for its reliable performance on individual identification but …
EEG feature fusion for motor imagery: A new robust framework towards stroke patients rehabilitation
Stroke is the second foremost cause of death worldwide and is one of the most common
causes of disability. Several approaches have been proposed to manage stroke patient …
causes of disability. Several approaches have been proposed to manage stroke patient …
A novel hybrid gene selection for tumor identification by combining multifilter integration and a recursive flower pollination search algorithm
M Li, L Ke, L Wang, S Deng, X Yu - Knowledge-Based Systems, 2023 - Elsevier
Gene selection is crucial to tumor identification based on microarray expression data. The
identification of genes with strong discriminative power has been a hot research topic and a …
identification of genes with strong discriminative power has been a hot research topic and a …
EEG temporal–spatial transformer for person identification
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 …
recognition since EEG signals are not easily stolen. Most of the existing studies on EEG …
Smart home battery for the multi-objective power scheduling problem in a smart home using grey wolf optimizer
The power scheduling problem in a smart home (PSPSH) refers to the timely scheduling
operations of smart home appliances under a set of restrictions and a dynamic pricing …
operations of smart home appliances under a set of restrictions and a dynamic pricing …
Dynamic coati optimization algorithm for biomedical classification tasks
Medical datasets are primarily made up of numerous pointless and redundant elements in a
collection of patient records. None of these characteristics are necessary for a medical …
collection of patient records. None of these characteristics are necessary for a medical …
Rank-driven salp swarm algorithm with orthogonal opposition-based learning for global optimization
Z Wang, H Ding, Z Yang, B Li, Z Guan, L Bao - Applied Intelligence, 2022 - Springer
Salp swarm algorithm (SSA) is a relatively new and straightforward swarm-based meta-
heuristic optimization algorithm, which is inspired by the flocking behavior of salps when …
heuristic optimization algorithm, which is inspired by the flocking behavior of salps when …
Automatic EEG channel selection for multiclass brain-computer interface classification using multiobjective improved firefly algorithm
A Tiwari, A Chaturvedi - Multimedia Tools and Applications, 2023 - Springer
Abstract Multichannel Electroencephalography-based Brain-Computer Interface (BCI)
systems facilitate a communicating medium between the human brain and the outside world …
systems facilitate a communicating medium between the human brain and the outside world …