Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Machine learning algorithms for epilepsy detection based on published EEG databases: A systematic review
Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …
Modified binary salp swarm algorithm in EEG signal classification for epilepsy seizure detection
Epilepsy is a brain disorder characterized by sudden seizures, periodic abnormal and
inappropriate behaviour, and an altered state of consciousness. The visual diagnosis of …
inappropriate behaviour, and an altered state of consciousness. The visual diagnosis of …
Effective early detection of epileptic seizures through EEG signals using classification algorithms based on t-distributed stochastic neighbor embedding and K-means
Epilepsy is a neurological disorder in the activity of brain cells that leads to seizures. An
electroencephalogram (EEG) can detect seizures as it contains physiological information of …
electroencephalogram (EEG) can detect seizures as it contains physiological information of …
Functional Classification of Spiking Signal Data Using Artificial Intelligence Techniques: A Review
Human brain neuron activities are incredibly significant nowadays. Neuronal behavior is
assessed by analyzing signal data such as electroencephalography (EEG), which can offer …
assessed by analyzing signal data such as electroencephalography (EEG), which can offer …
On the intersection of signal processing and machine learning: A use case-driven analysis approach
Recent advancements in sensing, measurement, and computing technologies have
significantly expanded the potential for signal-based applications, leveraging the synergy …
significantly expanded the potential for signal-based applications, leveraging the synergy …
Novel seizure detection algorithm based on multi-dimension feature selection
F Dong, Z Yuan, D Wu, L Jiang, J Liu, W Hu - Biomedical Signal Processing …, 2023 - Elsevier
In machine learning based seizure detection research studies, the number of features
directly affects the performance of models. In order to decrease the amount of features under …
directly affects the performance of models. In order to decrease the amount of features under …
Learning robust global-local representation from EEG for neural epilepsy detection
Epilepsy is a life-threatening and challenging neurological disorder, and applying an
electroencephalogram (EEG) is a commonly used clinical approach for its detection …
electroencephalogram (EEG) is a commonly used clinical approach for its detection …
Spatial-temporal-circulated GLCM and physiological features for in-vehicle people sensing based on IR-UWB radar
X Yang, Y Ding, X Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In-vehicle people sensing has received considerable attention for preventing overloading
and forgotten children. Impulse radio ultrawideband (IR-UWB) radar is widely applied in …
and forgotten children. Impulse radio ultrawideband (IR-UWB) radar is widely applied in …
A novel SVMA and K-NN classifier based optical ML technique for seizure detection
Among the most common paroxysmal neurological conditions is epilepsy. When
spontaneous combustion occurs seizure is a defining feature. An epileptic seizure is caused …
spontaneous combustion occurs seizure is a defining feature. An epileptic seizure is caused …
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis: A machine learning approach
Mosquito-borne diseases present considerable risks to the health of both animals and
humans. Aedes aegypti mosquitoes are the primary vectors for numerous medically …
humans. Aedes aegypti mosquitoes are the primary vectors for numerous medically …