Z
Zafer Iscan
Researcher at National Research University – Higher School of Economics
Publications - 25
Citations - 660
Zafer Iscan is an academic researcher from National Research University – Higher School of Economics. The author has contributed to research in topics: Feature extraction & Feature vector. The author has an hindex of 8, co-authored 24 publications receiving 559 citations. Previous affiliations of Zafer Iscan include Stony Brook University & Université Paris-Saclay.
Papers
More filters
Journal ArticleDOI
Classification of electroencephalogram signals with combined time and frequency features
TL;DR: Results show that the combination of the features derived from cross correlation and PSD is very promising in discriminating between epileptic and healthy EEG segments.
Journal ArticleDOI
Test–retest reliability of freesurfer measurements within and between sites: Effects of visual approval process
Zafer Iscan,Tony B. Jin,Alexandria Kendrick,Bryan C. Szeglin,Hanzhang Lu,Madhukar H. Trivedi,Maurizio Fava,Patrick J. McGrath,Myrna M. Weissman,Benji T. Kurian,Phillip Adams,Sarah Weyandt,Marisa Toups,Thomas J. Carmody,Melvin G. McInnis,Cristina Cusin,Crystal Cooper,Maria A. Oquendo,Ramin V. Parsey,Christine DeLorenzo,Christine DeLorenzo +20 more
TL;DR: To determine the effect of visual inspection on sample size required for studies of MRI‐derived cortical thickness, the number of subjects required to show group differences was calculated and significant differences observed across imaging sites, between visually approved/disapproved subjects, and across regions with different sizes suggest that these measures should be used with caution.
Journal ArticleDOI
Tumor detection by using Zernike moments on segmented magnetic resonance brain images
TL;DR: The proposed method for tumor detection in magnetic resonance (MR) brain images is investigated on one phantom and 20 original MR brain images with tumor and 50 normal (healthy) MR head images and it is observed that tumor detection is successfully realized.
Journal ArticleDOI
Steady state visual evoked potential (SSVEP) based brain-computer interface (BCI) performance under different perturbations.
TL;DR: This is the first study that systematically evaluates the effects of natural artifacts (i.e. mental, verbal and audio perturbations) on SSVEP-based BCIs and the results can be used to improve individual classification performance taking into account effects of perturbation.
Journal ArticleDOI
Pre-stimulus Alpha Oscillations and Inter-subject Variability of Motor Evoked Potentials in Single- and Paired-Pulse TMS Paradigms
Zafer Iscan,Maria Nazarova,Tommaso Fedele,Tommaso Fedele,Evgeny Blagovechtchenski,Evgeny Blagovechtchenski,Vadim V. Nikulin,Vadim V. Nikulin +7 more
TL;DR: The results show that the variability of the alpha oscillations can be more predictive of TMS effects than the commonly used power of oscillations and provide further support for the dissociation of high and low-alpha bands in predicting responses produced by the stimulation of the motor cortex.