| Estimating vigilance level by using EEG and EMG signals M Akin, MB Kurt, N Sezgin, M Bayram Neural Computing and Applications 17 (3), 227-236, 2008 | 202 | 2008 |
| Estimation of sleep stages by an artificial neural network employing EEG, EMG and EOG ME Tagluk, N Sezgin, M Akin Journal of medical systems 34 (4), 717-725, 2010 | 171 | 2010 |
| Classıfıcation of sleep apnea by using wavelet transform and artificial neural networks ME Tagluk, M Akin, N Sezgin Expert Systems with Applications 37 (2), 1600-1607, 2010 | 133 | 2010 |
| The ANN-based computing of drowsy level MB Kurt, N Sezgin, M Akin, G Kirbas, M Bayram Expert Systems with Applications 36 (2), 2534-2542, 2009 | 127 | 2009 |
| A new approach for estimation of obstructive sleep apnea syndrome ME Tagluk, N Sezgin Expert Systems with Applications 38 (5), 5346-5351, 2011 | 63 | 2011 |
| Energy based feature extraction for classification of sleep apnea syndrome N Sezgin, ME Tagluk Computers in biology and medicine 39 (11), 1043-1050, 2009 | 47 | 2009 |
| Analysis of EMG Signals in Aggressive and Normal Activities by Using Higher‐Order Spectra N Sezgin The Scientific World Journal 2012 (1), 478952, 2012 | 41 | 2012 |
| Classification of sleep apnea through sub-band energy of abdominal effort signal using wavelets+ neural networks ME Tagluk, N Sezgin Journal of medical systems 34, 1111-1119, 2010 | 32 | 2010 |
| A new hand finger movements’ classification system based on bicoherence analysis of two-channel surface EMG signals N Sezgin Neural Computing and Applications 31 (8), 3327-3337, 2019 | 31 | 2019 |
| Parameter estimation of solar cells via weighted mean of vectors algorithm D Izci, S Ekinci, S Dal, N Sezgin 2022 Global Energy Conference (GEC), 312-316, 2022 | 19 | 2022 |
| EMG classification in obstructive sleep apnea syndrome and periodic limb movement syndrome patients by using wavelet packet transform and extreme learning machine N Sezgin Turkish Journal of Electrical Engineering and Computer Sciences 23 (3), 873-884, 2015 | 18 | 2015 |
| A noninvasive time-frequency-based approach to estimate cuffless arterial blood pressure ÖF Ertuğrul, N Sezgin Turkish Journal of Electrical Engineering and Computer Sciences 26 (5), 2260 …, 2018 | 13 | 2018 |
| Nonlinear analysis of electrocardiography signals for atrial fibrillation N Sezgin The Scientific World Journal 2013 (1), 509784, 2013 | 12 | 2013 |
| Epileptik EG İşaretlerin Aşırı Öğrenme Makineleri ile Sınıflandırılması N Sezgin Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi 7 (3), 481-490, 2016 | 8 | 2016 |
| The correlation analysis between airflow and oxygen saturation in obstructive sleep apnea events using correlation function N Sezgin, G Kirbas, M Akin 2007 IEEE 15th Signal Processing and Communications Applications, 1-5, 2007 | 6 | 2007 |
| Determining of doze level analysing EEG signals by using wavelet transform and neural networks M Akin, M Bayram, O Eroglu, N Sezgin International XII., TAINN 1 (1), 2003 | 6 | 2003 |
| Classification of butterfly images with multi-scale local binary patterns Y Kaya, L Kayci, N Sezgin 2013 21st Signal Processing and Communications Applications Conference (SIU …, 2013 | 4 | 2013 |
| Using bispectral analysis in OSAS estimation N Sezgin, ME Tağluk, M Akın 2010 IEEE 18th Signal Processing and Communications Applications Conference …, 2010 | 4 | 2010 |
| Determining relevant features in estimating short-term power load of a small house via feature selection by extreme learning machine ÖF Ertuğrul, N Sezgin, A Öztekin, ME Tağluk 2017 International Artificial Intelligence and Data Processing Symposium …, 2017 | 3 | 2017 |
| ÖRÜNTÜ TANIMADA HOPFİELD AĞININ KULLANILMASI N Sezgin, R Tekin, A Çalışkan Batman Üniversitesi Yaşam Bilimleri Dergisi 1 (2), 257-266, 2012 | 3 | 2012 |