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Toplam kayıt 42, listelenen: 21-30
Dental enumeration and multiple treatment detection on panoramic X-rays using deep learning
(Nature Research, 2021)
In this paper, a new powerful deep learning framework, named as DENTECT, is developed in order to instantly detect five different dental treatment approaches and simultaneously number the dentition based on the FDI notation ...
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 ...
VLCnet: Deep learning based end-to-end visible light communication system
(IEEE-Institute of Electrical and Electronics Engineers Inc, 2020)
Visible light communication is a popular research area where proposed communication methods must satisfy the lighting related requirements as well. Suggested VLC modules should not only improve communication quality such ...
SNF-CVAE: Computational method to predict drug-disease interactions using similarity network fusion and collective variational autoencoder
(Elsevier, 2021)
Drug repositioning is an emerging approach to identify novel therapeutic potentials for approved drugs and discover therapies for previously untreatable diseases. Drug repositioning has also attracted considerable attention ...
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 ...
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 ...
Pancreatic tumor detection by convolutional neural networks
(Institute of Electrical and Electronics Engineers Inc., 2022)
Artificial Intelligence and its sub-branches like Machine Learning (ML) and Deep Learning (DL) applications have the potential to have positive effects that can directly affect human life. Medical imaging provides a way ...