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Toplam kayıt 8, listelenen: 1-8
Wi-Fi Based Indoor Positioning System with Using Deep Neural Network
(2020)
Indoor positioning is one of the major challenges for the future large-scale technologies. Nowadays, it has become an attractive research subject due to growing demands on it. Several algorithms and techniques have been ...
Diagnosis of Attention Deficit Hyperactivity Disorder with combined time and frequency features
(2020)
The aim of this study was to build a machine learning model to discriminate Attention Deficit Hyperactivity Disorder (ADHD) patients and healthy controls using information from both time and frequency analysis of Event ...
Evaluation of divided attention using different stimulation models in event-related potentials
(2019)
Divided attention is defined as focusing on different tasks at once, and this is described as one of the biggest problems of today's society. Default examinations for understanding attention are questionnaires or physiological ...
Deep neural network to differentiate brain activity between patients with euthymic bipolar disorders and healthy controls during verbal fluency performance: A multichannel near-infrared spectroscopy study
(2022)
In this study, we aimed to differentiate between euthymic bipolar disorder (BD) patients and healthy controls (HC) based on frontal activity measured by fNIRS that were converted to spectrograms with Convolutional Neural ...
Applications of Deep Learning Techniques to Wood Anomaly Detection
(2022)
Wood products and structures have an important place in today's industry. They are widely used in many fields. However, there are various difficulties in production systems where wood raw material is under many processes. ...
Detection of multiple sclerosis from photic stimulation EEG signals
(2021)
Background: Multiple Sclerosis (MS) is characterized as a chronic, autoimmune and inflammatory disease of the central nervous system. Early diagnosis of MS is of great importance for the treatment and course of the disease. ...
Obesity Level Estimation based on Machine Learning Methods and Artificial Neural Networks
(2021)
Obesity is a growing societal and public health problem starting from 1980 that needs more attention. For this reason, new studies are emerging day by day, including those looking for obesity in children, especially the ...
Investigation of some machine learning algorithms in fish age classification
(2021)
Marine and freshwater scientists use fish scales, vertebrae, otoliths and length-weights values to estimate fish age because reliable fish age estimation plays a very important role in fish stock management. The advances ...