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Toplam kayıt 23, listelenen: 11-20
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. ...
Modeling traders' behavior with deep learning and machine learning methods: Evidence from BIST 100 index
(Wiley-Hindawi, 2020)
Although the vast majority of fundamental analysts believe that technical analysts' estimates and technical indicators used in these analyses are unresponsive, recent research has revealed that both professionals and ...
SNF-NN: Computational method to predict drug-disease interactions using similarity network fusion and neural networks
(BioMed Central Ltd., 2021)
Background: Drug repositioning is an emerging approach in pharmaceutical research for identifying novel therapeutic potentials for approved drugs and discover therapies for untreated diseases. Due to its time and cost ...
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 ...
A survey of machine learning-based methods for COVID-19 medical image analysis
(Springer Science and Business Media Deutschland GmbH, 2023)
The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected after only 30 months since the first occurrences of the disease in December ...
A comparative study of different pre-trained deeplearning models and custom CNN for pancreatic tumor detection
(Zarka Private University, 2023)
Artificial Intelligence and its sub-branches like MachineLearning (ML) and Deep Learning (DL) applications have the potential to have positive effects that can directly affect human life. Medical imaging is briefly making ...
Exploring deep learning for adaptive energy detection threshold determination: A multistage approach
(Multidisciplinary Digital Publishing Institute (MDPI), 2023)
The concept of spectrum sensing has emerged as a fundamental solution to address the growing demand for accessing the limited resources of wireless communications networks. This paper introduces a straightforward yet ...