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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 ...
Orthogonal Extreme Learning Machine Based P300 Visual Event-Related BCI
(Springer, 2015)
Brain Computer Interface (BCI) is a type of human-computer relationship research that directly translates electrical activity of brain into commands that can rule equipment and create novel communication channel for muscular ...
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 ...
Beyin Bilgisayar Arayüzü Tabanli Görsel Tespit Sistemi
(Institute of Electrical and Electronics Engineers Inc., 2017)
Bu çalışmada görsel verilerin EEG sinyali üzerinde
meydana getirdiği p300 bileşeni kullanılarak örüntü tanıma tabanlı beyin bilgisayar ara yüzü geliştirilmiştir. EMOTIV EPOC+ kayıt cihazı ve OPENVIBE yazılımı kullanılarak ...
The experimental application of popular machine learning algorithms on predictive maintenance and the design of IIoT based condition monitoring system
(Elsevier, 2021)
With the fourth industrial revolution, which has become increasingly widespread in the manufacturing industry, traditional maintenance has been replaced by the industrial internet of things (IIoT) based on condition ...
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 with ConvNet Predicts Imagery Tasks Through EEG
(Springer, 2021)
Deep learning with convolutional neural networks (ConvNets) has dramatically improved the learning capabilities of computer vision applications just through considering raw data without any prior feature extraction. Nowadays, ...
Automatic segmentation of COVID-19 from computed tomography images using modified U-Net model-based majority voting approach
(Springer, 2022)
The coronavirus disease (COVID-19) is an important public health problem that has spread rapidly around the world and has caused the death of millions of people. Therefore, studies to determine the factors affecting the ...
Chronic obstructive pulmonary disease severity analysis using deep learning on multi-channel lung sounds
(Türkiye Klinikleri, 2020)
Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases which cannot be treated but can be kept under control in certain stages. COPD has five severities, including at-risk, mild, moderate, severe, ...
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 ...