Tuğba Özge Onur | Image Reconstruction | Best Researcher Award

Published on by Computer Vision Awards

Assoc. Prof. Dr. Tuğba Özge Onur | Image Reconstruction | Best Researcher Award

Associate Professor | Zonguldak Bülent Ecevit University | Turkey

Assoc. Prof. Dr. Tuğba Özge Onur is a distinguished researcher specializing in signal processing, image reconstruction, and optimization. She earned her Ph.D. in electrical and electronics engineering from a leading university, where she developed a strong foundation in computational imaging and algorithm design. Her professional experience includes leading research projects, coordinating international collaborations, and mentoring students in both academic and applied research settings. Her research interests span computer vision, optimization techniques, and advanced signal processing methods, with a focus on developing innovative solutions for real-world challenges. She possesses a diverse set of research skills, including algorithm development, data analysis, experimental design, and implementation of complex computational models. She is actively engaged in the scientific community through professional memberships and collaborative initiatives. Her work has been widely recognized and published in reputed journals and conferences, demonstrating both the depth and impact of her contributions. Her commitment to advancing knowledge, mentoring emerging researchers, and participating in collaborative projects underscores her influence in the field. 98 Citations, 23 Documents, 6 h-index.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Onur, T. Ö. (2022). Improved image denoising using wavelet edge detection based on Otsu’s thresholding. Acta Polytechnica Hungarica, 19(2), 79–92.

  2. Onur, Y. A., İmrak, C. E., & Onur, T. Ö. (2017). Investigation on bending over sheave fatigue life determination of rotation resistant steel wire rope. Experimental Techniques, 41(5), 475–482.

  3. Narin, D., & Onur, T. Ö. (2022). The effect of hyperparameters on the classification of lung cancer images using deep learning methods. Erzincan University Journal of Science and Technology, 15(1), 258–268.

  4. Kaya, G. U., & Onur, T. Ö. (2022). Genetic algorithm based image reconstruction applying the digital holography process with the Discrete Orthonormal Stockwell Transform technique for diagnosis of COVID-19. Computers in Biology and Medicine, 148, 105934.

  5. Onur, T. (2021). An application of filtered back projection method for computed tomography images. International Review of Applied Sciences and Engineering, 12(2), 194–200.