Ara
Toplam kayıt 9, listelenen: 1-9
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, ...
Identification of distorted RF components via deep multi-task learning
(Institute of Electrical and Electronics Engineers Inc., 2022)
High-quality radio frequency (RF) components are imperative for efficient wireless communication. However, these components can degrade over time and need to be identified so that either they can be replaced or their effects ...
rs-fMRI analysis using spatio-temporal sparse convolutional neural networks
(Institute of Electrical and Electronics Engineers Inc., 2022)
Neuropsychiatric diseases such as Autism Spectrum Disorder (ASD) and Schizophrenia cause various behavioral and communication dysfunctions in human life. Resting state functional magnetic resonance imaging (rs-fMRI) is ...
Predicting path loss distributions of a wireless communication system for multiple base station altitudes from satellite images
(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 ...