Ara
Toplam kayıt 21, listelenen: 11-20
Accurate detection of autism using Douglas-Peucker algorithm, sparse coding based feature mapping and convolutional neural network techniques with EEG signals
(Elsevier B.V. All, 2022)
Autism Spectrum Disorders (ASD) is a collection of complicated neurological disorders that first show in early childhood. Electroencephalogram (EEG) signals are widely used to record the electrical activities of the brain. ...
Radiomics and deep learning approach to the differential diagnosis of parotid gland tumors
(Wolters Kluwer Health, 2022)
All studies aimed at the differential diagnosis of benign vs. malignant PGTs or the identification of the
commonest PGT subtypes were identified, and five studies were found that focused on deep learning-based differential ...
A hybrid DNN–LSTM model for detecting phishing URLs
(Springer, 2021)
Phishing is an attack targeting to imitate the official websites of corporations such as banks, e-commerce, financial institutions, and governmental institutions. Phishing websites aim to access and retrieve users’ important ...
Investigation and prediction of ethylene Glycol based ZnO nanofluidic heat transfer versus magnetic effect by deep learning
(Elsevier Ltd, 2021)
In this study, ZnO (zinc oxide) nanoparticle production was performed. Heat transfer coefficients (h) were measured for Ethylene Glycol Based ZnO nanofluids that were produced using pure water, ethanol, and ethylene glycol ...
SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting
(Elsevier, 2021)
Photovoltaic (PV) power generation has high uncertainties due to the randomness and imbalance nature of solar energy and meteorological parameters. Hence, accurate PV power forecasts are essential in the operation of PV ...
A novel deep learning-based feature selection model for improving the static analysis of vulnerability detection
(Springer, 2021)
The automatic detection of software vulnerabilities is considered a complex and common research problem. It is possible to detect several security vulnerabilities using static analysis (SA) tools, but comparatively high ...
MTU-COVNet: A hybrid methodology for diagnosing the COVID-19 pneumonia with optimized features from multi-net
(elsevier, 2022)
Purpose
The aim of this study was to establish and evaluate a fully automatic deep learning system for the diagnosis of COVID-19 using thoracic computed tomography (CT).
Materials and methods
In this retrospective study, ...
When machine learning meets fractional-order chaotic signals: detecting dynamical variations
(Elsevier, 2022)
The challenge of classifying multivariate time series generated by discrete and continuous dynamical systems according to their chaotic or non-chaotic behavior has been studied extensively in the literature. The examination ...
Hurricane-Faster R-CNN-JS: Hurricane detection with faster R-CNN using artificial Jellyfish Search (JS) optimizer
(SPRINGER, 2022)
A hurricane is a type of storm called tropical cyclone (TC) and is likely to lead to severe storms and heavy rains. An early detection of hurricanes using satellite images can alarm people about upcoming disasters and thus ...
NCA-based hybrid convolutional neural network model for classification of cervical cancer on gauss-enhanced pap-smear images
(Wiley-Blackwell, 2022)
Cervical cancer is a very serious disease that deeply affects women's lives, often resulting in death. This type of cancer, which is very common in women, is diagnosed at an early stage and is of vital importance for the ...