Browsing by Author "Ateş, Hasan Fehmi"
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Analysis of deep learning based path loss prediction from satellite images
Alam, Muhammad Zeshan; Ateş, Hasan Fehmi; Baykaş, Tunçer; Güntürk, Bahadır Kürşat (Institute of Electrical and Electronics Engineers Inc., 2021)Determining the channel model parameters of a wireless communication system, either by measurements or by running electromagnetic propagation simulations, is a time-consuming process. Any rapid deployment of network demands ... -
A deep learning approach to permanent tooth germ detection on pediatric panoramic radiographs
Kaya, Emine; Güneç, Hüseyin Gürkan; Cesur Aydın, Kader; Ürkmez, Elif Şeyda; Duranay, Recep; Ateş, Hasan Fehmi (Korean Acad Oral and Maxillofacial Radiology, 2022)Purpose: The aim of this study was to assess the performance of a deep learning system for permanent tooth germ detection on pediatric panoramic radiographs.Materials and Methods: In total, 4518 anonymized panoramic ... -
Deep learning for inverse problems in imaging
Ateş, Hasan Fehmi (IEEE, 2019)Inverse problems have been widely studied in image processing, with applications in areas such as image denoising, blind/non-blind deblurring, super-resolution and compressive sensing. Lately deep learning techniques and ... -
Deep learning-based blind image super-resolution using iterative networks
Yaar, Asfand; Ateş, Hasan Fehmi; Güntürk, Bahadır Kürşat (Institute of Electrical and Electronics Engineers Inc., 2021)Deep learning-based single image super-resolution (SR) consistently shows superior performance compared to the traditional SR methods. However, most of these methods assume that the blur kernel used to generate the ... -
Dual camera based high spatio-temporal resolution video generation for wide area surveillance
Suluhan, Hasan Umut; Ateş, Hasan Fehmi; Güntürk, Bahadır Kürşat (Institute of Electrical and Electronics Engineers Inc., 2022)Wide area surveillance (WAS) requires high spatiotemporal resolution (HSTR) video for better precision. As an alternative to expensive WAS systems, low-cost hybrid imaging systems can be used. This paper presents the usage ... -
Efficient spectrum occupancy prediction exploiting multidimensional correlations through composite 2D-LSTM models
Aygül, Mehmet Ali; Nazzal, Mahmoud; Sağlam, Mehmet İzzet; da Costa, Daniel Benevides; Ateş, Hasan Fehmi; Arslan, Hüseyin (MDPI, 2021)In cognitive radio systems, identifying spectrum opportunities is fundamental to efficiently use the spectrum. Spectrum occupancy prediction is a convenient way of revealing opportunities based on previous occupancies. ... -
Geniş alan görüntülerinde anomali tespiti
Şahin, Abdullah Hamza; Ateş, Hasan Fehmi; Güntürk, Bahadır Kürşat (Institute of Electrical and Electronics Engineers Inc., 2021)Bu çalışma hava araçlarından çekilmiş geniş alan görüntülerindeki anomalileri tespit etmek ile ilgilidir. Anomali kümesi normal seyrin dışındaki her şey olarak belirlenmiştir. Bu amaçla iki farklı veri seti kullanılmış ve ... -
HM-net: A regression network for object center detection and tracking on wide area motion imagery
Motorcu, Hakkı; Ateş, Hasan Fehmi; Uğurdağ, Hasan Fatih; Güntürk, Bahadır Kürşat (IEEE-Institute of Electrical and Electronics Engineers Inc., 2022)Wide Area Motion Imagery (WAMI) yields high resolution images with a large number of extremely small objects. Target objects have large spatial displacements throughout consecutive frames. This nature of WAMI images makes ... -
Hybrid CPU-GPU acceleration of a multithreaded image stitching algorithm
Tesfay, Shewit W.; Demirdağ, Zeynep Gülbeyaz; Uğurdağ, H. Fatih; Ateş, Hasan Fehmi (Institute of Electrical and Electronics Engineers Inc., 2022)Real-time image stitching is critical, especially in un-manned aerial vehicles, and its acceleration has received attention in recent years. This paper describes an image stitching acceleration scheme for heterogeneous ... -
Improved YOLOv4 for aerial object detection
Ali, Sharoze; Siddique, Arslan; Ateş, Hasan Fehmi; Güntürk, Bahadır Kürşat (Institute of Electrical and Electronics Engineers Inc., 2021)Drones equipped with cameras are being used for surveillance purposes. These surveillance systems need vision-based object detection of ground objects which look very small because of the altitude of drones. We propose an ... -
Infrared-to-optical image translation for keypoint-based image registration
Elsaeidy, Mohamed; Erkol, Muhammed Emin; Güntürk, Bahadır Kürşat; Ateş, Hasan Fehmi (Institute of Electrical and Electronics Engineers Inc., 2022)Multi-modal image registration is a critical step in many remote sensing and visual navigation applications. While image registration techniques developed for single modality images do not perform well for multi-modal ... -
Learned vs. hand-crafted features for deep learning based aperiodic laboratory earthquake time-prediction
Zaidi, Talha; Samy, Asmaa; Kocatürk, Mehmet; Ateş, Hasan Fehmi (Institute of Electrical and Electronics Engineers Inc., 2020)Earthquakes cause the deadliest and most costly disasters among all natural hazards. Geophysicists and data scientists have spent a lot of effort, trying to predict earthquakes time, location or magnitude to minimize these ... -
Low-complexity deep learning-based beamforming in MISO systems
Thet, Nann Win Moe; Elgammal, Khaled Walid; Ateş, Hasan Fehmi; Özdemir, Mehmet Kemal (Institute of Electrical and Electronics Engineers Inc., 2021)This study proposes a low-complexity deep learning-based beamforming neural network (BFNN) for massive multiple-input single-output (MISO) systems. We adopt an unsupervised learning-based convolutional neural network (CNN) ... -
Multi-hypothesis contextual modeling for semantic segmentation
Ateş, Hasan Fehmi; Sünetçi, Sercan (Elsevier Science Bv, 2019)Semantic segmentation (i.e. image parsing) aims to annotate each image pixel with its corresponding semantic class label. Spatially consistent labeling of the image requires an accurate description and modeling of the local ... -
Path loss exponent and shadowing factor prediction from satellite images using deep learning
Ateş, Hasan Fehmi; Hashir, Syed Muhammad; Baykaş, Tuncer; Güntürk, Bahadır (Institute of Electrical and Electronics Engineers, 2019)Optimal network planning for wireless communication systems requires the detailed knowledge of the channel parameters of the target coverage area. Channel parameters can be estimated through extensive measurements in the ... -
PL-GAN: Path loss prediction using generative adversarial networks
Marey, Ahmed; Bal, Mustafa; Ateş, Hasan Fehmi; Güntürk, Bahadır Kürşat (IEEE-Institute of Electrical and Electronics Engineers Inc., 2022)Accurate prediction of path loss is essential for the design and optimization of wireless communication networks. Existing path loss prediction methods typically suffer from the trade-off between accuracy and computational ... -
Predicting path loss distribution of an area from satellite ımages using deep learning
Ahmadien, Omar; Ateş, Hasan Fehmi; Baykaş, Tunçer; Güntürk, Bahadır Kürşat (IEEE - Institute of Electrical and Electronics Engineers, Inc., 2020)Path loss prediction is essential for network planning in any wireless communication system. For cellular networks, it is usually achieved through extensive received signal power measurements in the target area. When the ... -
Predicting path loss distributions of a wireless communication system for multiple base station altitudes from satellite images
Shoer, İbrahim; Güntürk, Bahadır Kürşat; Ateş, Hasan Fehmi; Baykaş, Tunçer (IEEE Computer Society, 2022)It is expected that unmanned aerial vehicles (UAVs) will play a vital role in future communication systems. Optimum positioning of UAVs, serving as base stations, can be done through extensive field measurements or ray ... -
Proposing a CNN method for primary and permanent tooth detection and enumeration on pediatric dental radiographs
Kaya, Emine; Güneç, Hüseyin Gürkan; Gökyay, Sıtkı Selçuk; Kutal, Seçilay; Gülüm, Semih; Ateş, Hasan Fehmi (NLM (Medline), 2022)OBJECTIVE: In this paper, we aimed to evaluate the performance of a deep learning system for automated tooth detection and numbering on pediatric panoramic radiographs. STUDY DESIGN: YOLO V4, a CNN (Convolutional Neural ... -
Regression of large-scale path loss parameters using deep neural networks
Bal, Mustafa; Marey, Ahmed; Ateş, Hasan Fehmi; Baykaş, Tunçer; Güntürk, Bahadır Kürşat (IEEE-Institute of Electrical and Electronics Engineers Inc., 2022)Path loss exponent and shadowing factor are among important wireless channel parameters. These parameters can be estimated using field measurements or ray-tracing simulations, which are costly and time-consuming. In this ...
