Konu "Deep learning" için WoS İndeksli Yayınlar Koleksiyonu listeleme
Toplam kayıt 19, listelenen: 1-19
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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. ... -
Classification of thermoluminescence features of CaCO3 with long short-term memory model
(Wiley, 2021)Calcium carbonate (CaCO3 ), a mineral commonly found in the Earth's crust, is mainly in the forms of calcite and aragonite. Calcite has the most stable type of thermodynamics at room temperature and ambient pressure. It ... -
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 ... -
COVIDiagnosis-Net: Deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from X-ray images
(Elsevier, 2020)The Coronavirus Disease 2019 (COVID-19) outbreak has a tremendous impact on global health and the daily life of people still living in more than two hundred countries. The crucial action to gain the force in the fight of ... -
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 ... -
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 ... -
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 ... -
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 ... -
An improved residual-based convolutional neural network for very short-term wind power forecasting
(ELSEVIER, 2021)An accurate forecast of wind power is very important in terms of economic dispatch and the operation of power systems. However, effectively mitigating the risks arising from wind power in power system operations greatly ... -
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 ... -
Is it useful to use computerized tomography image-based artificial intelligence modelling in the differential diagnosis of chronic otitis media with and without cholesteatoma?
(Elsevier B.V. All, 2022)Cholesteatoma is an aggressive form of chronic otitis media (COM). For this reason, it is important to distinguish between COM with and without cholesteatoma. In this study, the role of artificial intelligence modelling ... -
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) -
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, ... -
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 ... -
Prediction of software vulnerability based deep symbiotic genetic algorithms: Phenotyping of dominant-features
(2021)The detection of software vulnerabilities is considered a vital problem in the software security area for a long time. Nowadays, it is challenging to manage software security due to its increased complexity and diversity. ... -
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 ... -
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 ... -
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 ... -
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 ...