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Toplam kayıt 10, listelenen: 1-10
Prediction of preference and effect of music on preference: a preliminary study on electroencephalography from young women
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, ATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA, 00000, TURKEY, 2019)
Neuromarketing is the application of the neuroscientific approaches to analyze and understand economically relevant behavior. In this study, the effect of loud and rhythmic music in a sample neuromarketing setup is ...
Medical infrared thermal image based fatty liver classification using machine and deep learning
(TAYLOR & FRANCIS LTD, 2023)
Non-alcoholic fatty liver disease (NAFLD) causes accumulation of excess fat in the liver affecting people who drink little to no alcohol. Non-alcoholic steatohepatitis (NASH) is an aggressive form of fatty liver disease ...
Split-attention effects in multimedia learning environments: eye-tracking and EEG analysis
(SPRINGER, 2022)
This study aimed to evaluate the split-attention effect in multimedia learning environments via objective measurements as EEG and eye-tracking. Two different multimedia
learning environments in a focused (integrated) and ...
Improved classification of colorectal polyps on histopathological images with ensemble learning and stain normalization
(ELSEVIER IRELAND, 2023)
Background and Objective: Early detection of colon adenomatous polyps is critically important because correct detection of it significantly reduces the potential of developing colon cancers in the future. The key challenge ...
An FDTD-based computer simulation platform for shock wave propagation in electrohydraulic lithotripsy
(ELSEVIER, 2013)
Extracorporeal Shock Wave Lithotripsy (ESWL) is based on disintegration of the kidney stone
by delivering high-energy shock waves that are created outside the body and transmitted
through the skin and body tissues. ...
Like/dislike analysis using EEG: Determination of most discriminative channels and frequencies
(ELSEVIER IRELAND LTD, 2014)
In this study, we have analyzed electroencephalography (EEG) signals to investigate the following issues, (i) which frequencies and EEG channels could be relatively better indicators of preference (like or dislike decisions) ...
Liver fibrosis staging using CT image texture analysis and soft computing
(ELSEVIER, 2014)
Liver biopsy is considered to be the gold standard for analyzing chronic hepatitis and fibrosis; however, it is an invasive and expensive approach, which is also difficult to standardize. Medical imaging
techniques such ...
Transfer Learning for P300 Brain-Computer Interfaces by Joint Alignment of Feature Vectors
(IEEE, 2023)
This article presents a new transfer learning
method named group learning, that jointly aligns multiple domains (many-to-many) and an extension named fast
alignment that aligns any further domain to previously
aligned ...
A new tool for QT interval analysis during sleep in healthy and obstructive sleep apnea subjects: a study on women
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, ATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA, 00000, TURKEY, 2013)
By monitoring the Q wave/T wave (QT) interval computed from electrocardiography (ECG) signals during sleep, it is possible to create a link between the ventricular repolarization and sleep stages. In this study, we aimed ...
An effective colorectal polyp classification for histopathological images based on supervised contrastive learning
(ELSEVIER, 2024)
Early detection of colon adenomatous polyps is pivotal in reducing colon cancer risk. In this context, accurately distinguishing between adenomatous polyp subtypes, especially tubular and tubulovillous, from hyperplastic ...