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Muhammed Talo
Muhammed Talo
Bestätigte E-Mail-Adresse bei firat.edu.tr
Titel
Zitiert von
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Jahr
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
25642020
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
5002019
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
3932019
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
2932020
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
2732019
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
2442020
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
2092019
Automated Classification of Histopathology Images Using Transfer Learning
M Talo
Artificial Intelligence in Medicine, 101743, 2019
166*2019
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
1392019
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
892020
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
882021
1D-CADCapsNet: One dimensional deep capsule networks for coronary artery disease detection using ECG signals
E Butun, O Yildirim, M Talo, RS Tan, UR Acharya
Physica Medica 70, 39-48, 2020
682020
Evaluating deep learning models for sentiment classification
B Ay Karakuş, M Talo, İR Hallaç, G Aydin
Concurrency and Computation: Practice and Experience 30 (21), e4783, 2018
672018
Review of deep learning-based atrial fibrillation detection studies
F Murat, F Sadak, O Yildirim, M Talo, E Murat, M Karabatak, Y Demir, ...
International journal of environmental research and public health 18 (21), 11302, 2021
492021
An automated deep learning approach for bacterial image classification
M Talo
arXiv preprint arXiv:1912.08765, 2019
332019
Exploring deep features and ECG attributes to detect cardiac rhythm classes
F Murat, O Yildirim, M Talo, Y Demir, RS Tan, EJ Ciaccio, UR Acharya
Knowledge-Based Systems 232, 107473, 2021
302021
Naming a channel with beeps
BS Chlebus, G De Marco, M Talo
Fundamenta Informaticae 153 (3), 199-219, 2017
282017
Pneumonia detection from radiography images using convolutional neural networks
M Talo
2019 27th Signal Processing and Communications Applications Conference (SIU …, 2019
182019
Automatic semantic segmentation for dental restorations in panoramic radiography images using U‐Net model
F Oztekin, O Katar, F Sadak, M Aydogan, TT Yildirim, P Plawiak, O Yildirim, ...
International Journal of Imaging Systems and Technology 32 (6), 1990-2001, 2022
92022
Deep learning-based PI-RADS score estimation to detect prostate cancer using multiparametric magnetic resonance imaging
K Yildirim, M Yildirim, H Eryesil, M Talo, O Yildirim, M Karabatak, ...
Computers and Electrical Engineering 102, 108275, 2022
92022
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