| 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 | 2671 | 2020 |
| 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 | 769 | 2018 |
| 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 | 720 | 2018 |
| 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 | 524 | 2019 |
| 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 | 412 | 2019 |
| 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 | 326 | 2019 |
| 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 | 320 | 2017 |
| 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 | 306 | 2020 |
| 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 | 291 | 2019 |
| 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 | 263 | 2020 |
| 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 | 237 | 2019 |
| 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 | 225 | 2019 |
| An efficient compression of ECG signals using deep convolutional autoencoders O Yildirim, R San Tan, UR Acharya Cognitive Systems Research 52, 198-211, 2018 | 213 | 2018 |
| 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 | 190 | 2020 |
| 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 | 143 | 2019 |
| 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 | 135 | 2013 |
| 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 | 128 | 2017 |
| 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 | 101 | 2021 |
| 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 | 100 | 2014 |
| 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 | 93 | 2020 |
Rajendra AcharyaProfessor, University of Southern Queensland; Cogninet Australia Pty Ltd, Australia在 usq.edu.au 的电子邮件经过验证
