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PUBLICATIONS

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JOURNAL PAPERS

  • Suluhan, H.U., Doruk, A.E., Ates, H.F. et al. Hstr-net: reference based video super-resolution with dual cameras. Machine Vision and Applications 36, 69 (2025). https://doi.org/10.1007/s00138-025-01685-w
  • Guven, Gokce, H. F. Ugurdag, Hasan F. Ates. “X2BR: High-Fidelity 3D Bone Reconstruction from a Planar X-Ray Image with Hybrid Neural Implicit Methods.” ArXiv abs/2504.08675 (2025).
  • A. Enes Doruk and Hasan F. Ates. “DA-Mamba: Domain Adaptive Hybrid Mamba-Transformer Based One-Stage Object Detection”, Arxiv abs/2502.11178 (2025).
  • A Enes Doruk, Hasan F Ates, “DAViMNet: SSMs-Based Domain Adaptive Object Detection”, arXiv: 2502.11178, 2025.
  • A Enes Doruk, Erhan Oztop, Hasan F Ates, “TransAdapter: Vision Transformer for Feature-Centric Unsupervised Domain Adaptation”, arXiv: 2412.04073. 2024.
  • Ismail Can Yagmur, Hasan F Ates, Bahadir K Gunturk, “XPoint: A Self-Supervised Visual-State-Space based Architecture for Multispectral Image Registration”, arXiv:2411.07430. 2024
  • Emine Kaya, Hüseyin Gürkan Güneç, Elif Şeyda Ürkmez, Kader Cesur Aydın, Hasan Fehmi, “Deep learning for diagnostic charting on pediatric panoramic radiographs,” International Journal of Computerized Dentistry, 27-3, 2024.
  • G. Guven, H. F. Ates and H. F. Ugurdag, “X2V: 3D Organ Volume Reconstruction From a Planar X-Ray Image With Neural Implicit Methods,” in IEEE Access, vol. 12, pp. 50898-50910, 2024.
  • Sıtkı Selçuk Gökyay, Hüseyin Gürkan Güneç, Hasan Fehmi Ates, “Application of an Artificial-Intelligence Algorithm for the Enumeration of Teeth and the Detection of Multiple Dental Diseases”, Medical Journal of Europe, 2024
  • Umut Suluhan, H., Ates, H. F., & Gunturk, B. K. (2023). HSTR-Net: Reference Based Video Super-resolution for Aerial Surveillance with Dual Cameras. arXiv e-prints, arXiv-2310.
  • Ates, H. F., Yildirim, S., & Gunturk, B. K. (2023). Deep learning-based blind image super-resolution with iterative kernel reconstruction and noise estimation. Computer Vision and Image Understanding, 233, 103718.
  • Kaya, E., Güneç, H. G., Ürkmez, E. Ş., & Ateş, H. F. (2023). Deep Learning for Diagnostic Charting on Pediatric Panoramic Radiographs. International Journal of Computerized Dentistry, 0-0.
  • Ates, H. F., Siddique, A., & Gunturk, B. (2023). HMRN: heat map regression network to detect and track small objects in wide-area motion imagery. Signal, Image and Video Processing, 17(1), 39-45.
  • Kaya, E., Gunec, H. G., Aydin, K. C., Urkmez, E. S., Duranay, R., & Ates, H. F. (2022). A deep learning approach to permanent tooth germ detection on pediatric panoramic radiographs. Imaging science in dentistry, 52(3), 275.
  • Marey, A., Bal, M., Ates, H. F., & Gunturk, B. K. (2022). Pl-gan: Path loss prediction using generative adversarial networks. IEEE Access, 10, 90474-90480.
  • Karakusak, M. Z., Kivrak, H., Ates, H. F., & Ozdemir, M. K. (2022). Rss-based wireless lan indoor localization and tracking using deep architectures. Big Data and Cognitive Computing, 6(3), 84.
  • Kaya, E., Gunec, H. G., Gokyay, S. S., Kutal, S., Gulum, S., & Ates, H. F. (2022). Proposing a CNN method for primary and permanent tooth detection and enumeration on pediatric dental radiographs. Journal of Clinical Pediatric Dentistry, 46(4), 293-298.
  • Bal, M., Marey, A., Ates, H. F., Baykas, T., & Gunturk, B. K. (2022). Regression of large-scale path loss parameters using deep neural networks. IEEE Antennas and Wireless Propagation Letters, 21(8), 1562-1566.
  • Motorcu, H., Ates, H. F., Ugurdag, H. F., & Gunturk, B. K. (2021). Hm-net: A regression network for object center detection and tracking on wide area motion imagery. IEEE Access, 10, 1346-1359.
  • Aygül, M. A., Nazzal, M., Sağlam, M. İ., da Costa, D. B., Ateş, H. F., & Arslan, H. (2020). Efficient spectrum occupancy prediction exploiting multidimensional correlations through composite 2D-LSTM models. Sensors, 21(1), 135.
  • Ahmadien, Omar, et al. “Predicting path loss distribution of an area from satellite images using deep learning.” IEEE Access 8 (2020): 64982-64991.
  • Ates, Hasan F., et al. “Path loss exponent and shadowing factor prediction from satellite images using deep learning.” IEEE Access 7 (2019): 101366-101375.

CONFERENCE PAPERS

  • D. Berk, M. Adak, B. Adak, C. Celik and H. F. Ateş, “Real-Time Multi-Object Tracking with YOLOv8,” 2024 32nd Signal Processing and Communications Applications Conference (SIU), Mersin, Turkiye, 2024, pp. 1-4, doi: 10.1109/SIU61531.2024.10600933.
  • Yağmur, İ. C., & Ates, H. F. (2023, October). Improved homographic adaptation for keypoint generation in cross-spectral registration of thermal and optical imagery. In Image and Signal Processing for Remote Sensing XXIX (Vol. 12733, pp. 67-73). SPIE.
  • Şahin, A. H., & Ateş, H. F. (2023, September). Deep learning based event recognition in aerial imagery. In 2023 8th International Conference on Computer Science and Engineering (UBMK) (pp. 426-431). IEEE.
  • Elsaeidy, M., Yağmur, İ. C., Ateş, H. F., & Güntürk, B. K. (2023, July). Swin transformer based siamese network for thermal and optical image registration. In 2023 31st Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.
  • Suluhan, H. U., Ates, H. F., & Gunturk, B. K. (2022, November). Dual camera based high spatio-temporal resolution video generation for wide area surveillance. In 2022 18th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (pp. 1-8). IEEE.
  • Shoer, I., Gunturk, B. K., Ates, H. F., & Baykas, T. (2022, October). Predicting path loss distributions of a wireless communication system for multiple base station altitudes from satellite images. In 2022 IEEE International Conference on Image Processing (ICIP) (pp. 2471-2475). IEEE.
  • Yildirim, S., Ates, H. F., & Gunturk, B. K. (2022, October). Iterative kernel reconstruction for deep learning-based blind image super-resolution. In 2022 IEEE International Conference on Image Processing (ICIP) (pp. 3251-3255). IEEE.
  • Tesfay, S. W., Demirdag, Z. G., Ugurdag, H. F., & Ates, H. F. (2022, September). Hybrid CPU-GPU acceleration of a multithreaded image stitching algorithm. In 2022 7th International Conference on Computer Science and Engineering (UBMK) (pp. 468-473). IEEE.
  • Elsaeidy, M., Erkol, M. E., Güntürk, B. K., & Ateş, H. F. (2022, May). Infrared-to-optical image translation for keypoint-based image registration. In 2022 30th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.
  • Yaar, A., Ates, H. F., & Gunturk, B. K. (2021, December). Deep learning-based blind image super-resolution using iterative networks. In 2021 International Conference on Visual Communications and Image Processing (VCIP) (pp. 01-05). IEEE.
  • Aktaş, M., & Ateş, H. F. (2021, September). Small object detection and tracking from aerial imagery. In 2021 6th International Conference on Computer Science and Engineering (UBMK) (pp. 688-693). IEEE.
  • Alam, M. Z., Ates, H. F., Baykas, T., & Gunturk, B. K. (2021, June). Analysis of deep learning based path loss prediction from satellite images. In 2021 29th signal processing and communications applications conference (SIU) (pp. 1-4). IEEE.
  • Şahın, A. H., Ateş, H. F., & Güntürk, B. K. (2021, June). Anomaly Detection in Wide Area Imagery. In 2021 29th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.
  • Ali, S., Siddique, A., Ateş, H. F., & Güntürk, B. K. (2021, June). Improved YOLOv4 for aerial object detection. In 2021 29th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.
  • Thet, N. W. M., Elgammal, K. W., Ates, H. F., & Ozdemir, M. K. (2021, June). Low-complexity deep learning-based beamforming in MISO systems. In 2021 29th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.
  • Şahin, A. H., Ateş, H. F., & Güntürk, B. K. (2021). Geniş alan görüntülerinde anomali tespiti. In 29th IEEE Conference on Signal Processing and Communications Applications, SIU. Institute of Electrical and Electronics Engineers Inc..
  • Zaidi, T., Samy, A., Kocatürk, M., & Ateş, H. F. (2020, October). Learned vs. hand-crafted features for deep learning based aperiodic laboratory earthquake time-prediction. In 2020 28th signal processing and communications applications conference (SIU) (pp. 1-4). IEEE.
  • Aygül, M. A., Büyükçorak, S., da Costa, D. B., Ateş, H. F., & Arslan, H. (2020, June). Signal relation-based physical layer authentication. In ICC 2020-2020 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.
  • Aygül, M. A., Nazzal, M., Ekti, A. R., Görçin, A., da Costa, D. B., Ateş, H. F., & Arslan, H. (2020, May).
    Spectrum occupancy prediction exploiting time and frequency correlations through 2D-LSTM. In 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring) (pp. 1-5). IEEE.