[HTML][HTML] Decoding brain signals: A convolutional neural network approach for motor imagery classification

O Tarahi, S Hamou, M Moufassih, S Agounad… - e-Prime-Advances in …, 2024‏ - Elsevier
Motor imagery-centered brain-computer interfaces (BCIs) have surfaced as a promising
technology with the potential to improve communication and control for people facing motor …

Detection method of epileptic seizures using a neural network model based on multimodal dual-stream networks

B Wang, Y Xu, S Peng, H Wang, F Li - Sensors, 2024‏ - mdpi.com
Epilepsy is a common neurological disorder, and its diagnosis mainly relies on the analysis
of electroencephalogram (EEG) signals. However, the raw EEG signals contain limited …

A novel method for optimizing epilepsy detection features through multi-domain feature fusion and selection

G Kong, S Ma, W Zhao, H Wang, Q Fu… - Frontiers in …, 2024‏ - frontiersin.org
Background The methods used to detect epileptic seizures using electroencephalogram
(EEG) signals suffer from poor accuracy in feature selection and high redundancy. This …

[PDF][PDF] Forecasting the consumer price index: a comparative study of machine learning methods

FN Sibai, A El-Moursy, A Sibai - International Journal of …, 2024‏ - researchgate.net
The Consumer Price Index (CPI) is an indicator of inflation and is tracked by many
government and economic agencies to make decisions of major importance. Its prediction is …

Seizure detection using nonlinear measures over EEG frequency bands and deep learning classifiers

A Benzaid, R Djemili, K Arbateni - Computer Methods in …, 2024‏ - Taylor & Francis
Epilepsy is a brain disorder that causes patients to suffer from convulsions, which affects
their behavior and way of life. Epilepsy can be detected with electroencephalograms …

Advancing Epilepsy Disease Classification through Machine Learning and Deep Learning Models Utilizing EEG Data.

A Saleem, MA Khan, HM Yousaf - 2023 17th International …, 2023‏ - ieeexplore.ieee.org
Epilepsy disease is a neurological condition marked by recurring seizures that has a big
effect on people's life. Effective management and therapy depend on a prompt and correct …

Enhancing the evaluation performance of convolutional neural networks-based vehicle classification systems

MP Kiyindou, SE Sunday, Z Hong - … Conference on the …, 2023‏ - ieeexplore.ieee.org
The rapid advancement of artificial intelligence, particularly deep learning, has spurred its
integration into diverse domains. Among these, the application of deep learning in vehicle …

AstroSer: Leveraging Deep Learning for Efficient Content-based Retrieval in Massive Solar-observation Images

S Wu, Y Liu, L Yang, X Liu, X Li, Y **ang… - Publications of the …, 2023‏ - iopscience.iop.org
Rapid and proficient data retrieval is an essential component of modern astronomical
research. In this paper, we address the challenge of retrieving astronomical image content …

Adaptive Multi-feature Attention Neural Tree for EEG-based Fatigue Detection

Q Li, D Wang - 2024 IEEE 12th International Conference on …, 2024‏ - ieeexplore.ieee.org
Driver fatigue assessment is important to traffic safety, and the gold standard for fatigue
detection is widely regarded as the EEG signals. Traditional machine learning methods fall …

[PDF][PDF] e-Prime-Advances in Electrical Engineering, Electronics and Energy

B Papari, L Timilsina, A Moghassemi, AA Khan…‏ - researchgate.net
This paper discusses the growing influence of renewable energy and distributed generation,
emphasizing the need for smart control systems to maximize benefits and optimize network …