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Case Study: Deep Convolutional Networks in Healthcare
(Springer Verlag, 2020)
Technological improvements lead big data producing, processing and storing systems. These systems must contain extraordinary capabilities to overcome complexity of the big data. Therefore, the methodologies utilized for ...
Estimation of daily global solar radiation using deep learning model
(Elsevier, 2018)
Solar radiation (SR) is an important data for various applications such as climate, energy and engineering. Because of this, determination and estimation of temporal and spatial variability of SR has critical importance ...
A Multistage Deep Learning Algorithm for Detecting Arrhythmia
(Institute of Electrical and Electronics Engineers, 2018)
Deep Belief Networks (DBN) is a deep learning algorithm that has both greedy layer-wise unsupervised and supervised training. Arrhythmia is a cardiac irregularity caused by a problem of the heart. In this study, a multi-stage ...
Performance Comparision of Different Momentum Techniques on Deep Reinforcement Learning
(Institute of Electrical and Electronics Engineers Inc., 2017)
Increase in popularity of deep convolutional neural networks in many different areas leads to increase in the use of these networks in reinforcement learning. Training a huge deep neural network structure by using simple ...
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 ...
Deep Learning for COPD Analysis Using Lung Sounds
(Baku State University, 2018)
In this study, Hilbert-Huang Transform (HHT) was applied to the lung sounds from RespiratoryDatabase@TR and the statistical features were calculated from the different modulations of the HHT. The statistical features were ...
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 ...
A deep learning architecture for identification of breast cancer on mammography by learning various representations of cancerous mass
(Springer, 2021)
Deep Learning (DL) is a high capable machine learning algorithm with the detailed analysis abilities on images. Although DL models achieve very high classification performances, the applications are trending on using and ...
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 ...