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Toplam kayıt 9, listelenen: 1-9
Electrocardiogram beat classification using deep convolutional neural network techniques
(Institute of Physics Publishing, 2020)
The electrocardiogram (ECG) is a useful method which enables the monitoring of various cardiac conditions, such as arrhythmia and heart rate variability (HRV). ECG beats help to determine various heart failures such as ...
Classification of physical actions from surface EMG signals using the wavelet packet transform and local binary patterns
(Institute of Physics Publishing, 2020)
Physical action recognition is a hot topic in human-machine interactions. It has potential uses in helping disabled people and in various robotic applications. Electromyography (EMG) signals measure the electrical activity ...
Long Short-Term Memory Network-based Speed Estimation Model of an Asynchronous Motor
(IEEE (Institute of Electrical and Electronics Engineers), 2021)
In this paper, an effective deep rotor speed estimation model of an asynchronous motor is presented. The estimation model is based on the long short-term memory (LSTM) network which is one of the deep learning models. The ...
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 New Framework for Automatic Detection of Patients With Mild Cognitive Impairment Using Resting-State EEG Signals
(IEEE (Institute of Electrical and Electronics Engineers), 2020)
Mild cognitive impairment (MCI) can be an indicator representing the early stage of Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major public health problem worldwide. Efficient detection ...
A New Signal to Image Mapping Procedure and Convolutional Neural Networks for Efficient Schizophrenia Detection in EEG Recordings
(Institute of Electrical and Electronics Engineers Inc., 2022)
Machine learning has been densely used in most computer-aided medical diagnosis systems. These systems not only supported the physician’s decision but also accelerate the necessitated procedures. Electroencephalography ...
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 ...
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 ...
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 ...