Coronavirus (Covid-19) Classification Using CT Images by Machine Learning Methods M Barstuğan, U Özkaya, Ş Öztürk Recent Trends and Applications in Computer Science and Information …, 2021 | 566* | 2021 |
Coronavirus (COVID-19) classification using deep features fusion and ranking technique U Özkaya, Ş Öztürk, M Barstuğan Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation …, 2020 | 221 | 2020 |
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 | 180 | 2021 |
Deep learning-based weathering type recognition in historical stone monuments ME Hatir, M Barstuğan, İ İnce Journal of Cultural Heritage 45, 193-203, 2020 | 72 | 2020 |
PBO/graphene added β-PVDF piezoelectric composite nanofiber production R Barstugan, M Barstugan, I Ozaytekin Composites Part B: Engineering 158, 141-148, 2019 | 43 | 2019 |
COVID-19 discrimination framework for X-ray images by considering radiomics, selective information, feature ranking, and a novel hybrid classifier H Koyuncu, M Barstuğan Signal Processing: Image Communication 97, 116359, 2021 | 17 | 2021 |
The effect of dictionary learning on weight update of AdaBoost and ECG classification M Barstuğan, R Ceylan Journal of King Saud University-Computer and Information Sciences 32 (10 …, 2020 | 17 | 2020 |
Evaluation of the relationship between the physical properties and capillary water absorption values of building stones by regression analysis and artificial neural networks İ İnce, A Bozdağ, M Barstuğan, M Fener Journal of Building Engineering 42, 103055, 2021 | 15 | 2021 |
Adrenal tumor segmentation method for MR images M Barstuğan, R Ceylan, S Asoglu, H Cebeci, M Koplay Computer methods and programs in biomedicine 164, 87-100, 2018 | 15 | 2018 |
A comprehensive study of brain tumour discrimination using phase combinations, feature rankings, and hybridised classifiers H Koyuncu, M Barstuğan, MÜ Öziç Medical & Biological Engineering & Computing 58, 2971-2987, 2020 | 13 | 2020 |
Automatic Liver Segmentation in Abdomen CT Images using SLIC and AdaBoost Algorithms M Barstuğan, R Ceylan, M Sivri, H Erdoğan 8th International Conference on Bioscience, Biochemistry, and Bioinformatics …, 2018 | 12 | 2018 |
Adrenal tumor characterization on magnetic resonance images M Barstugan, R Ceylan, S Asoglu, H Cebeci, M Koplay Journal of Imaging Systems and Technology, 1-14, 2019 | 8 | 2019 |
Coronavirus (COVID-19) classification using CT ımages by machine learning methods. eprint M Barstugan, U Ozkaya, S Ozturk arXiv preprint arXiv:2003.09424, 2020 | 7 | 2020 |
Detection of defects on single-bead welding by machine learning methods M Barstugan, YS Ceran, M Yilmaz, NA Dundar IOP Conference Series: Materials Science and Engineering 895 (1), 012012, 2020 | 5 | 2020 |
An autonomous system design for mold loading on press brake machines using a camera platform, deep learning, and image processing MÜ Öziç, M Barstuğan, A Özdamar Journal of Mechanical Science and Technology 37 (8), 4239-4247, 2023 | 4 | 2023 |
A Deep Learning-Based Quality Control Application M Korkmaz, M Barstuğan Avrupa Bilim ve Teknoloji Dergisi, 332-336, 2020 | 4 | 2020 |
A New Breakpoint to Classify 3D Voxels in MRI: A Space Transform Strategy with 3t2FTS-v2 and Its Application for ResNet50-Based Categorization of Brain Tumors H Koyuncu, M Barstuğan Bioengineering 10 (6), 629, 2023 | 3 | 2023 |
Deep Learning Based Human Robot Interaction with 5G Communication M BARSTUĞAN, Z OSMANPAŞAOĞLU Konya Journal of Engineering Sciences 11 (2), 423-438, 2023 | 3 | 2023 |
Rotor fault characterization study by considering normalization analysis, feature extraction, and a multi-class classifier M Barstuğan, H Arabacı Engineering Research Express 6 (2), 025304, 2024 | 2 | 2024 |
Feature Selection using FFS and PCA in Biomedical Data Classification with AdaBoost-SVM R Ceylan, M Barstuğan International Journal of Intelligent Systems and Applications in Engineering …, 2018 | 2 | 2018 |