Özal Yildirim
Orcid: 0000-0001-5375-3012
According to our database1,
Özal Yildirim
authored at least 27 papers
between 2012 and 2023.
Collaborative distances:
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Bibliography
2023
Application of Kronecker convolutions in deep learning technique for automated detection of kidney stones with coronal CT images.
Inf. Sci., September, 2023
2022
Efficient deep neural network model for classification of grasp types using sEMG signals.
J. Ambient Intell. Humaniz. Comput., 2022
Automatic semantic segmentation for dental restorations in panoramic radiography images using U-Net model.
Int. J. Imaging Syst. Technol., 2022
Classification and Self-Supervised Regression of Arrhythmic ECG Signals Using Convolutional Neural Networks.
CoRR, 2022
Electrochemical Biosensing and Deep Learning-Based Approaches in the Diagnosis of COVID-19: A Review.
IEEE Access, 2022
2021
Knowl. Based Syst., 2021
Comput. Biol. Medicine, 2021
Deep Neural Network Trained on Surface ECG Improves Diagnostic Accuracy of Prior Myocardial Infarction Over Q Wave Analysis.
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021
2020
Automated invasive ductal carcinoma detection based using deep transfer learning with whole-slide images.
Pattern Recognit. Lett., 2020
A deep convolutional neural network model for automated identification of abnormal EEG signals.
Neural Comput. Appl., 2020
Accurate deep neural network model to detect cardiac arrhythmia on more than 10, 000 individual subject ECG records.
Comput. Methods Programs Biomed., 2020
Comput. Biol. Medicine, 2020
Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review.
Comput. Biol. Medicine, 2020
2019
Pattern Recognit. Lett., 2019
Deep long short-term memory networks-based automatic recognition of six different digital modulation types under varying noise conditions.
Neural Comput. Appl., 2019
Automated Depression Detection Using Deep Representation and Sequence Learning with EEG Signals.
J. Medical Syst., 2019
Application of deep transfer learning for automated brain abnormality classification using MR images.
Cogn. Syst. Res., 2019
A new approach for arrhythmia classification using deep coded features and LSTM networks.
Comput. Methods Programs Biomed., 2019
Convolutional neural networks for multi-class brain disease detection using MRI images.
Comput. Medical Imaging Graph., 2019
Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals.
Comput. Biol. Medicine, 2019
An Implementation of Vision Based Deep Reinforcement Learning for Humanoid Robot Locomotion.
Proceedings of the IEEE International Symposium on INnovations in Intelligent SysTems and Applications, 2019
2018
Application of Computational Intelligence Methods for the Automated Identification of Paper-Ink Samples Based on LIBS.
Sensors, 2018
Cogn. Syst. Res., 2018
Arrhythmia detection using deep convolutional neural network with long duration ECG signals.
Comput. Biol. Medicine, 2018
A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.
Comput. Biol. Medicine, 2018
2015
Proceedings of the 2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015
2012
Proceedings of the 20th Signal Processing and Communications Applications Conference, 2012