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Toplam kayıt 17, listelenen: 1-10
The analysis of text categorization represented with word embeddings using homogeneous classifiers
(Institute of Electrical and Electronics Engineers Inc., 2019)
Text data mining is the process of extracting and analyzing valuable information from text. A text data mining process generally consists of lexical and syntax analysis of input text data, the removal of non-informative ...
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, ...
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 ...
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 ...
An improved demand forecasting model using deep learning approach and proposed decision integration strategy for supply chain
(Wiley-Hindawi, 2019)
Demand forecasting is one of the main issues of supply chains. It aimed to optimize stocks, reduce costs, and increase sales, profit, and customer loyalty. For this purpose, historical data can be analyzed to improve demand ...
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. ...