Takip et
Özal YILDIRIM
Özal YILDIRIM
firat.edu.tr üzerinde doğrulanmış e-posta adresine sahip
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
Automated detection of COVID-19 cases using deep neural networks with X-ray images
T Ozturk, M Talo, EA Yildirim, UB Baloglu, O Yildirim, UR Acharya
Computers in biology and medicine 121, 103792, 2020
26382020
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
Ö Yıldırım, P Pławiak, RS Tan, UR Acharya
Computers in biology and medicine 102, 411-420, 2018
7592018
A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification
Ö Yildirim
Computers in biology and medicine 96, 189-202, 2018
7092018
Application of deep transfer learning for automated brain abnormality classification using MR images
M Talo, UB Baloglu, Ö Yıldırım, UR Acharya
Cognitive Systems Research 54, 176-188, 2019
5162019
Classification of myocardial infarction with multi-lead ECG signals and deep CNN
UB Baloglu, M Talo, O Yildirim, R San Tan, UR Acharya
Pattern recognition letters 122, 23-30, 2019
4072019
A new approach for arrhythmia classification using deep coded features and LSTM networks
O Yildirim, UB Baloglu, RS Tan, EJ Ciaccio, UR Acharya
Computer methods and programs in biomedicine 176, 121-133, 2019
3252019
Face recognition based on convolutional neural network
M Coşkun, A Uçar, Ö Yildirim, Y Demir
2017 international conference on modern electrical and energy systems (MEES …, 2017
3192017
Automated invasive ductal carcinoma detection based using deep transfer learning with whole-slide images
Y Celik, M Talo, O Yildirim, M Karabatak, UR Acharya
Pattern Recognition Letters 133, 232-239, 2020
3032020
Convolutional neural networks for multi-class brain disease detection using MRI images
M Talo, O Yildirim, UB Baloglu, G Aydin, UR Acharya
Computerized Medical Imaging and Graphics 78, 101673, 2019
2852019
Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review
F Murat, O Yildirim, M Talo, UB Baloglu, Y Demir, UR Acharya
Computers in biology and medicine 120, 103726, 2020
2562020
A deep learning model for automated sleep stages classification using PSG signals
O Yildirim, UB Baloglu, UR Acharya
International journal of environmental research and public health 16 (4), 599, 2019
2332019
Automated depression detection using deep representation and sequence learning with EEG signals
B Ay, O Yildirim, M Talo, UB Baloglu, G Aydin, SD Puthankattil, ...
Journal of medical systems 43, 1-12, 2019
2242019
An efficient compression of ECG signals using deep convolutional autoencoders
O Yildirim, R San Tan, UR Acharya
Cognitive Systems Research 52, 198-211, 2018
2112018
A deep convolutional neural network model for automated identification of abnormal EEG signals
Ö Yıldırım, UB Baloglu, UR Acharya
Neural Computing and Applications 32 (20), 15857-15868, 2020
1862020
Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals
O Yildirim, M Talo, B Ay, UB Baloglu, G Aydin, UR Acharya
Computers in biology and medicine 113, 103387, 2019
1422019
Optimal feature selection for classification of the power quality events using wavelet transform and least squares support vector machines
H Erişti, Ö Yıldırım, B Erişti, Y Demir
International Journal of Electrical Power & Energy Systems 49, 95-103, 2013
1332013
An overview of popular deep learning methods
M Coşkun, Ö Yıldırım, A Uçar, Y Demır
European Journal of Technique (EJT) 7 (2), 165-176, 2017
1272017
Automatic recognition system of underlying causes of power quality disturbances based on S-Transform and Extreme Learning Machine
H Erişti, Ö Yıldırım, B Erişti, Y Demir
International Journal of Electrical Power & Energy Systems 61, 553-562, 2014
1002014
Deep learning model for automated kidney stone detection using coronal CT images
K Yildirim, PG Bozdag, M Talo, O Yildirim, M Karabatak, UR Acharya
Computers in biology and medicine 135, 104569, 2021
962021
Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records
O Yildirim, M Talo, EJ Ciaccio, R San Tan, UR Acharya
Computer methods and programs in biomedicine 197, 105740, 2020
922020
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