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Toplam kayıt 13, listelenen: 1-10
Diagnosis and grading of vesicoureteral reflux on voiding cystourethrography images in children using a deep hybrid model
(Elsevier, 2021)
Background and objective
Vesicoureteral reflux is the leakage of urine from the bladder into the ureter. As a result, urinary tract infections and kidney scarring can occur in children. Voiding cystourethrography is the ...
MTU-COVNet: A hybrid methodology for diagnosing the COVID-19 pneumonia with optimized features from multi-net
(Elsevier, 2022)
COVID-19PneumoniaArtificial intelligence (AI)Deep learningComputed tomography (CT)
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 ...
Comparison of extreme learning machine and deep learning model in the estimation of the fresh properties of hybrid fiber-reinforced SCC
(Springer, 2021)
This paper studied the estimation of fresh properties of hybrid fiber-reinforced self-compacting concrete (HR-SCC) mixtures with different types and combinations of fibers by using two different prediction method named as ...
Deep learning model developed by multiparametric MRI in differential diagnosis of parotid gland tumors
(Springer, 2022)
Purpose: To create a new artificial intelligence approach based on deep learning (DL) from multiparametric MRI in the differential diagnosis of common parotid tumors. Methods: Parotid tumors were classified using the ...
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, ...
SEM-Net: Deep features selections with Binary Particle Swarm Optimization Method for classification of scanning electron microscope images
(Elsevier, 2021)
Materials Science is increasingly handling artificial intelligence methods to address the complexity in the field of everyday life necessities. Researchers in both academia and industry are interested in imaging techniques ...
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 ...
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 ...
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 ...