Automated epilepsy detection techniques from electroencephalogram signals: a review study
Epilepsy is a serious neurological condition which contemplates as top 5 reasons for
avoidable mortality from ages 5–29 in the worldwide. The avoidable deaths due to epilepsy …
avoidable mortality from ages 5–29 in the worldwide. The avoidable deaths due to epilepsy …
Deep learning-based multi-head self-attention model for human epilepsy identification from EEG signal for biomedical traits
The neurological condition epilepsy is demanding and even fatal. Electroencephalogram
(EEG)-based epilepsy detection still faces various difficulties. EEG readings fluctuate, and …
(EEG)-based epilepsy detection still faces various difficulties. EEG readings fluctuate, and …
[HTML][HTML] COVID-19 detection using chest X-ray images based on a developed deep neural network
Aim Currently, a new coronavirus called COVID-19 is the biggest challenge of the human at
21st century. Now, the spread of this virus is such that mortality has risen strongly in all cities …
21st century. Now, the spread of this virus is such that mortality has risen strongly in all cities …
Developing a deep neural network for driver fatigue detection using EEG signals based on compressed sensing
In recent years, driver fatigue has become one of the main causes of road accidents. As a
result, fatigue detection systems have been developed to warn drivers, and, among the …
result, fatigue detection systems have been developed to warn drivers, and, among the …
Automatic detection of driver fatigue based on EEG signals using a developed deep neural network
In recent years, detecting driver fatigue has been a significant practical necessity and issue.
Even though several investigations have been undertaken to examine driver fatigue, there …
Even though several investigations have been undertaken to examine driver fatigue, there …
Dictionary learning-based damage detection under varying environmental conditions using only vibration responses of numerical model and real intact State …
Monitoring structural damage is critical for preserving the service life of engineering systems.
In varying operational environments, the working loads are changing all the time and they …
In varying operational environments, the working loads are changing all the time and they …
Epileptic classification with deep-transfer-learning-based feature fusion algorithm
J Cao, D Hu, Y Wang, J Wang… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Epilepsy ictal detection based on scalp electroencephalograms (EEGs) has been
comprehensively studied in the past decades. But few attentions have been paid to the …
comprehensively studied in the past decades. But few attentions have been paid to the …
[HTML][HTML] Developing an efficient deep neural network for automatic detection of COVID-19 using chest X-ray images
S Sheykhivand, Z Mousavi, S Mojtahedi… - Alexandria Engineering …, 2021 - Elsevier
Abstract The novel coronavirus (COVID-19) could be described as the greatest human
challenge of the 21st century. The development and transmission of the disease have …
challenge of the 21st century. The development and transmission of the disease have …
Automatic seizure detection and classification using super-resolution superlet transform and deep neural network-A preprocessing-less method
Context Epilepsy, characterized by recurrent seizures, is a chronic brain disease that affects
approximately 50 million. Recurrent seizures characterize it. A seizure, a burst of …
approximately 50 million. Recurrent seizures characterize it. A seizure, a burst of …
A review of the classification of neuroscience problems with the help of Deep Learning Framework
Electroencephalographic signals (EEG signals) processing has become very popular
nowadays due to its effectiveness in dealing with and treating various disorders associated …
nowadays due to its effectiveness in dealing with and treating various disorders associated …