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LU triangularization extreme learning machine in EEG cognitive task classification
(Springer, 2019)
Electroencephalography (EEG) has been used as a promising tool for investigation of brain activity during cognitive processes. The aim of this study is to reveal whether EEG signals can be used for classifying cognitive ...
Deep Convolutional Generalized Classifier Neural Network
(Springer, 2020)
Up to date technological implementations of deep convolutional neural networks are at the forefront of many issues, such as autonomous device control, effective image and pattern recognition solutions. Deep neural networks ...
SecureDeepNet-IoT: A deep learning application for invasion detection in industrial Internet of Things sensing systems
(Wiley, 2021)
Deep learning (DL) is a special field of artificial intelligence that has increased its use in various fields and has proved its effectiveness in classification. The feasibility of using many hidden layers and many neurons ...
Differential convolutional neural network
(Elsevier, 2019)
Convolutional neural networks with strong representation ability of deep structures have ever increasing popularity in many research areas. The main difference of Convolutional Neural Networks with respect to existing ...
Deep Learning on Computerized Analysis of Chronic Obstructive Pulmonary Disease
(Institute of Electrical and Electronics Engineers Inc., 2020)
Goal: Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases in the world. Because COPD is an incurable disease and requires considerable time to be diagnosed even by an experienced specialist, it ...