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Toplam kayıt 17, listelenen: 1-10
Learned vs. hand-crafted features for deep learning based aperiodic laboratory earthquake time-prediction
(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 ...
Deep learning-assisted detection of PUE and jamming attacks in cognitive radio systems
(Institute of Electrical and Electronics Engineers Inc., 2020)
Cognitive radio (CR)-based internet of things systems can be considered as an efficient solution for futuristic smart technologies. However, CRs are naturally vulnerable to two major security threats; primary user emulation ...
Geniş alan görüntülerinde anomali tespiti
(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 ...
Improved YOLOv4 for aerial object detection
(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 ...
Deep learning-based optimal ris interaction exploiting previously sampled channel correlations
(IEEE - Institute of Electrical and Electronics Engineers, Inc, 2021)
The reconfigurable intelligent surface (RIS) technology has attracted interest due to its promising coverage and spectral efficiency features. However, some challenges need to be addressed to realize this technology in ...
Joint estimation of multiple RF impairments using deep multi-task learning
(IEEE-Institute of Electrical and Electronics Engineers Inc., 2022)
Radio-frequency (RF) front-end forms a critical part of any radio system, defining its cost as well as communication performance. However, these components frequently exhibit non-ideal behavior, referred to as impairments, ...
Intelligent spectrum occupancy prediction for realistic measurements: GRU based approach
(Institute of Electrical and Electronics Engineers Inc., 2022)
Cognitive radio (CR) technology has always been a research hotspot in the wireless communications field as it has the potential to significantly improve system capacity at the cost of increased processing time and power ...
Rotten-fruit-sorting robotic arm: (Design of low complexity cnn for embedded system)
(MDPI, 2022)
Industrial Automation has revolutionized the processing industry due to its high accuracy, the time it saves, and its ability to work without tiring. Being the most fundamental part of automation machines, robotic arms are ...
PL-GAN: Path loss prediction using generative adversarial networks
(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
(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 ...