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Toplam kayıt 14, listelenen: 1-10
A new approach to early diagnosis of congestive heart failure disease by using Hilbert-Huang transform
(Elsevier Ireland Ltd., 2016)
Congestive heart failure (CHF) is a degree of cardiac disease occurring as a result of the heart's inability to pump enough blood for the human body. In recent studies, coronary artery disease (CAD) is accepted as the most ...
Deep learning with 3D-second order difference plot on respiratory sounds
(Elsevier, 2018)
The second order difference plot (SODP) is a nonlinear signal analysis method that visualizes two consecutive data points for many types of biomedical signals. The proposed method is based on analysing quantization of ...
DeepGraphNet: Grafiklerin Sınıflandırılmasında Derin Öğrenme Modelleri
(Avrupa Bilim ve Teknoloji Dergisi, 2019)
Grafik sınıflandırma modeli henüz yeni bir araştırma alanı olarak ön plana çıkan bir görüntü işleme yaklaşımıdır. Özellikle verilerin görselleştirilmesi ve kolay okunabilirliğini sağlamak için tercih edilen grafikler, ...
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 ...
Deep Learning-based Mammogram Classification for Breast Cancer
(International Journal of Intelligent Systems and Applications in Engineering, 2020)
Deep Learning (DL) is a rising field of researches in last decade by exposing a hybrid analysis procedure including advanced level image processing and many efficient supervised classifiers. Robustness of the DL algorithms ...
ECG based human identification using Second Order Difference Plots
(Elsevier, 2019)
Background and objective: ECG is one of the biometric signals that has been studied in peer-reviewed over past years. The developments on the signal analysis methods show that the studies on the ECG would continue unabatedly. ...
A fully distributed energy-aware multi-level clustering and routing for WSN-based IoT
(Wiley, 2021)
One of the major problems in wireless sensor networks (WSNs) is that resource-constrained sensor nodes consume their limited batteries quickly due to long-distance data communications. The communication distance of the ...
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, ...
A novel fractional operator application for neural networks using proportional Caputo derivative
(Springer, 2022)
In machine learning models, one of the most popular models is artificial neural networks. The activation function is one of the important parameters of neural networks. In this paper, the sigmoid function is used as an ...
DeepOCT: An explainable deep learning architecture to analyze macular edema on OCT images
(Elsevier, 2022)
Macular edema (ME) is one of the most common retinal diseases that occur as a result of the detachment of the retinal layers on the macula. This study provides computer-aided identification of ME for even small pathologies ...