[HTML][HTML] Aviation and neurophysiology: A systematic review
This paper systematically reviews 20 years of publications (N= 54) on aviation and
neurophysiology. The main goal is to provide an account of neurophysiological changes …
neurophysiology. The main goal is to provide an account of neurophysiological changes …
Machine learning protocols in early cancer detection based on liquid biopsy: a survey
With the advances of liquid biopsy technology, there is increasing evidence that body fluid
such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor …
such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor …
A wavelet packet transform-based deep feature transfer learning method for bearing fault diagnosis under different working conditions
Deep learning has achieved significant advances in the fault diagnosis of rotating
machinery. However, it still suffers many challenges such as various working conditions …
machinery. However, it still suffers many challenges such as various working conditions …
A new many-objective evolutionary algorithm based on generalized Pareto dominance
In the past several years, it has become apparent that the effectiveness of Pareto-dominance-
based multiobjective evolutionary algorithms deteriorates progressively as the number of …
based multiobjective evolutionary algorithms deteriorates progressively as the number of …
Driver distraction detection using bidirectional long short-term network based on multiscale entropy of EEG
Driver distraction diverting drivers' attention to unrelated tasks and decreasing the ability to
control vehicles, has aroused widespread concern about driving safety. Previous studies …
control vehicles, has aroused widespread concern about driving safety. Previous studies …
Alzheimer's disease diagnosis with brain structural mri using multiview-slice attention and 3D convolution neural network
Numerous artificial intelligence (AI) based approaches have been proposed for automatic
Alzheimer's disease (AD) prediction with brain structural magnetic resonance imaging …
Alzheimer's disease (AD) prediction with brain structural magnetic resonance imaging …
Deep learning in lane marking detection: A survey
Y Zhang, Z Lu, X Zhang, JH Xue… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Lane marking detection is a fundamental but crucial step in intelligent driving systems. It can
not only provide relevant road condition information to prevent lane departure but also assist …
not only provide relevant road condition information to prevent lane departure but also assist …
Brain-computer interface using brain power map and cognition detection network during flight
This article presents a new aviation brain-computer interface, which includes the
construction of a color brain power map and a cognitive detection network. The developed …
construction of a color brain power map and a cognitive detection network. The developed …
Quantitative combination load forecasting model based on forecasting error optimization
Accurate load forecasting is indispensable in various applications of the electric power
industry. Although existing load forecasting methods perform well, they cannot handle …
industry. Although existing load forecasting methods perform well, they cannot handle …
An external‐validated prediction model to predict lung metastasis among osteosarcoma: a multicenter analysis based on machine learning
Background. Lung metastasis greatly affects medical therapeutic strategies in
osteosarcoma. This study aimed to develop and validate a clinical prediction model to …
osteosarcoma. This study aimed to develop and validate a clinical prediction model to …