Coronavirus (covid-19) classification using ct images by machine learning methods M Barstugan, U Ozkaya, S Ozturk arXiv preprint arXiv:2003.09424, 2020 | 492 | 2020 |
Coronavirus (COVID-19) classification using deep features fusion and ranking technique U Özkaya, Ş Öztürk, M Barstugan Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation …, 2020 | 211 | 2020 |
Application of feature extraction and classification methods for histopathological image using GLCM, LBP, LBGLCM, GLRLM and SFTA Ş Öztürk, B Akdemir Procedia computer science 132, 40-46, 2018 | 190 | 2018 |
Unsupervised medical image translation with adversarial diffusion models M Özbey, O Dalmaz, SUH Dar, HA Bedel, Ş Özturk, A Güngör, T Çukur IEEE Transactions on Medical Imaging, 2023 | 167 | 2023 |
Classification of Coronavirus (COVID‐19) from X‐ray and CT images using shrunken features Ş Öztürk, U Özkaya, M Barstuğan International Journal of Imaging Systems and Technology 31 (1), 5-15, 2021 | 157 | 2021 |
Skin lesion segmentation with improved convolutional neural network Ş Öztürk, U Özkaya Journal of digital imaging 33, 958-970, 2020 | 111 | 2020 |
Adaptive diffusion priors for accelerated MRI reconstruction A Güngör, SUH Dar, Ş Öztürk, Y Korkmaz, HA Bedel, G Elmas, M Ozbey, ... Medical Image Analysis 88, 102872, 2023 | 98 | 2023 |
Stacked auto-encoder based tagging with deep features for content-based medical image retrieval Ş Öztürk Expert Systems with Applications 161, 113693, 2020 | 87 | 2020 |
Comparison of edge detection algorithms for texture analysis on glass production Ş Öztürk, B Akdemir Procedia-Social and Behavioral Sciences 195, 2675-2682, 2015 | 86 | 2015 |
Variants of Artificial Bee Colony algorithm and its applications in medical image processing Ş Öztürk, R Ahmad, N Akhtar Applied Soft Computing 97, 106799, 2020 | 74 | 2020 |
Residual LSTM layered CNN for classification of gastrointestinal tract diseases Ş Öztürk, U Özkaya Journal of Biomedical Informatics 113, 103638, 2021 | 70 | 2021 |
A novel hybrid deep learning approach including combination of 1D power signals and 2D signal images for power quality disturbance classification H Sindi, M Nour, M Rawa, Ş Öztürk, K Polat Expert Systems with Applications 174, 114785, 2021 | 68 | 2021 |
Gastrointestinal tract classification using improved LSTM based CNN Ş Öztürk, U Özkaya Multimedia Tools and Applications 79 (39), 28825-28840, 2020 | 63 | 2020 |
HIC-net: A deep convolutional neural network model for classification of histopathological breast images Ş Öztürk, B Akdemir Computers & Electrical Engineering 76, 299-310, 2019 | 53 | 2019 |
Coronavirus (covid-19) classification using ct images by machine learning methods. arXiv 2020 M Barstugan, U Ozkaya, S Ozturk arXiv preprint arXiv:2003.09424, 0 | 48 | |
Deep clustering via center-oriented margin free-triplet loss for skin lesion detection in highly imbalanced datasets Ş Öztürk, T Çukur IEEE Journal of Biomedical and Health Informatics 26 (9), 4679-4690, 2022 | 46 | 2022 |
Effects of histopathological image pre-processing on convolutional neural networks Ş Öztürk, B Akdemir Procedia computer science 132, 396-403, 2018 | 46 | 2018 |
Residual CNN+ Bi-LSTM model to analyze GPR B scan images U Özkaya, Ş Öztürk, F Melgani, L Seyfi Automation in Construction 123, 103525, 2021 | 44 | 2021 |
Class-driven content-based medical image retrieval using hash codes of deep features Ş Öztürk Biomedical Signal Processing and Control 68, 102601, 2021 | 39 | 2021 |
Random fully connected layered 1D CNN for solving the Z-bus loss allocation problem H Sindi, M Nour, M Rawa, Ş Öztürk, K Polat Measurement 171, 108794, 2021 | 35 | 2021 |