Browsing by Author "Özer, Sedat"
Now showing items 1-8 of 8
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Deep receiver design for multi-carrier waveforms using CNNs
(IEEE, 2020)In this paper, a deep learning based receiver is proposed for a collection of multi-carrier wave-forms including both current and next-generation wireless communication systems. In particular, we propose to use a convolutional ... -
GRJointNET: 3B eksik nokta bulutları için sinerjistik tamamlama ve parça bölütleme
(IEEE, 2021-07-19)Üç boyutlu (3B) nokta bulutları üzerinde bölütleme yapmak, otonom sistemler için önemli ve gerekli bir işlemdir. Bölütleme algoritmalarının başarısı, üzerinde işlem yapılan nokta bulutlarının niteliğine (çözünürlük, ... -
Offloading deep learning empowered image segmentation from UAV to edge server
(IEEE, 2021-08-30)Image and video analysis in unmanned aerial vehicle (UAV) systems have been a recent interest in many applications since the images taken by UAV systems can provide useful information in many domains including maintenance, ... -
Simultaneous prediction of remaining-useful-life and failure-likelihood with GRU-based deep networks for predictive maintenance analysis
(IEEE, 2021-08-30)Predictive maintenance (PdM) has been an integral part of large industrial sites collecting data from multiple sensors to reduce the maintenance power and costs with the advent of Industry 4.0. Two of the major problems ... -
SyNet: an ensemble network for object detection in UAV images
(IEEE, 2021-05-05)Recent advances in camera equipped drone applications and their widespread use increased the demand on vision based object detection algorithms for aerial images. Object detection process is inherently a challenging task ... -
Visual object tracking in drone images with deep reinforcement learning
(IEEE, 2021-05-05)There is an increasing demand on utilizing camera equipped drones and their applications in many domains varying from agriculture to entertainment and from sports events to surveillance. In such drone applications, an ... -
YOLODrone+: improved YOLO architecture for object detection in UAV images
(IEEE, 2022-08-29)The performance of object detection algorithms running on images taken from Unmanned Aerial Vehicles (UAVs) remains limited when compared to the object detection algorithms running on ground taken images. Due to its various ... -
YOLODrone: improved YOLO architecture for object detection in drone images
(IEEE, 2021-08-30)Recent advances in robotics and computer vision fields yield emerging new applications for camera equipped drones. One such application is aerial-based object detection. However, despite the recent advances in the relevant ...
