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Toplam kayıt 7, listelenen: 1-7
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 ...
Path loss exponent and shadowing factor prediction from satellite images using deep learning
(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 ...
Proposing a CNN method for primary and permanent tooth detection and enumeration on pediatric dental radiographs
(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 ...
Efficient spectrum occupancy prediction exploiting multidimensional correlations through composite 2D-LSTM models
(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. ...
Regression of large-scale path loss parameters using deep neural networks
(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 ...
HMRN: heat map regression network to detect and track small objects in wide-area motion imagery
(Springer Science and Business Media Deutschland GmbH, 2023)
We propose HMRN, a deep heat map regression network to detect and track small moving objects in wide-area motion imagery (WAMI) by modifying a deep multi-object tracker. Object detection in WAMI images is challenging, ...