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[HTML][HTML] Decoding brain signals: A convolutional neural network approach for motor imagery classification
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 …
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 …
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 …
(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
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 …
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
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 …
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.
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 …
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 …
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 …
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 …
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 …
emphasizing the need for smart control systems to maximize benefits and optimize network …