Yayıncı "Elsevier" Elektrik-Elektronik Mühendisliği Bölümü Koleksiyonu için listeleme
Toplam kayıt 8, listelenen: 1-8
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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 rhythm and long short term memory-based drowsiness detection
(Elsevier, 2021)In this paper, a deep-rhythm-based approach is proposed for the efficient detection of drowsiness based on EEG recordings. In the proposed approach, EEG images are used instead of signals where the time and frequency ... -
An efficient fault classification method in solar photovoltaic modules using transfer learning and multi-scale convolutional neural network
(Elsevier, 2022)Photovoltaic (PV) power generation is one of the remarkable energy types to provide clean and sustainable energy. Therefore, rapid fault detection and classification of PV modules can help to increase the reliability of ... -
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) -
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 ... -
WSFNet: An efficient wind speed forecasting model using channel attention-based densely connected convolutional neural network
(Elsevier, 2021)This paper introduces a novel deep neural network (WSFNet) to efficiently forecast multi-step ahead wind speed. WSFNet forms the basis of the stacked convolutional neural network (CNN) with dense connections of different ...