Yazar "Avcı, Mutlu" için listeleme
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Case Study: Deep Convolutional Networks in Healthcare
Avcı, Mutlu; Sarıgül, Mehmet; Özyıldırım, Buse Melis (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 ... -
Deep Convolutional Generalized Classifier Neural Network
Sarıgül, Mehmet; Özyıldırım, Buse Melis; Avcı, Mutlu (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 ... -
Differential convolutional neural network
Sarıgül, Mehmet; Özyıldırım, Buse Melis; Avcı, Mutlu (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 ... -
Estimation of daily global solar radiation using deep learning model
Kaba, Kazım; Sarıgül, Mehmet; Avcı, Mutlu; Kandırmaz, H. Mustafa (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 ... -
Performance Comparision of Different Momentum Techniques on Deep Reinforcement Learning
Sarıgül, Mehmet; Avcı, Mutlu (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 ... -
Q Learning Regression Neural Network
Sarıgül, Mehmet; Avcı, Mutlu (Neural Network World, 2018)In this work, a Nadaraya-Watson kernel based learning system which owns general regression neural network topology is adapted to Q learning method to evaluate a quick and efficient action selection policy for reinforcement ...