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ORCIDOnder Aydemir
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2020 – today
- 2024
[j12]Amir Naser, Önder Aydemir:
Enhancing EEG Signal Classification With a Novel Random Subset Channel Selection Approach: Applications in Taste, Odor, and Motor Imagery Analysis. IEEE Access 12: 145608-145618 (2024)- [j11]Onur Erdem Korkmaz
, Sevde Gül Korkmaz, Onder Aydemir:
Detection of multitask mental workload using gamma band power features. Neural Comput. Appl. 36(18): 10915-10926 (2024) - [c28]Fatih Aydin, Sefer Usta, Mehmet Öztürk, Özge Aydogdu, Ezgi KalaycioGLu, Önder Aydemir:
High Accuracy Detection of S and T Peaks in ECG Signals. SIU 2024: 1-4 - 2023
- [j10]Amir Naser, Onder Aydemir:
Classification of pleasant and unpleasant odor imagery EEG signals. Neural Comput. Appl. 35(12): 9105-9114 (2023) - [j9]Onur Erdem Korkmaz, Onder Aydemir, Emin Argun Oral, Ibrahim Yucel Ozbek:
A novel probabilistic and 3D column P300 stimulus presentation paradigm for EEG-based spelling systems. Neural Comput. Appl. 35(16): 11901-11915 (2023) - [j8]Ebru Ergün, Onder Aydemir:
A Hybrid BCI Using Singular Value Decomposition Values of the Fast Walsh-Hadamard Transform Coefficients. IEEE Trans. Cogn. Dev. Syst. 15(2): 454-463 (2023) - 2021
- [j7]Bilge Han Tozlu, Cemaleddin Simsek, Onder Aydemir, Yusuf Karavelioglu:
A High performance electronic nose system for the recognition of myocardial infarction and coronary artery diseases. Biomed. Signal Process. Control. 64: 102247 (2021) - [j6]Onder Aydemir:
A New Performance Evaluation Metric for Classifiers: Polygon Area Metric. J. Classif. 38(1): 16-26 (2021) - [j5]Onur Erdem Korkmaz, Onder Aydemir, Emin Argun Oral, Ibrahim Yucel Ozbek:
Investigating the Effect of COVID-19 Infection on P300 Based BCI Application Performance. Traitement du Signal 38(6): 1767-1773 (2021) - [c27]Tugba Aydemir, Mehmet Sahin, Önder Aydemir:
Gender Recognition from PPG Signals of People with Different Blood Pressure. SIU 2021: 1-4 - 2020
- [j4]Onder Aydemir:
Odor and Subject Identification Using Electroencephalography Reaction to Olfactory. Traitement du Signal 37(5): 799-805 (2020) - [c26]Önder Aydemir, Amir Naser, Mehmet Öztürk:
Classification of EEG Signals Recorded While Imagining Odors with Effective Band Pass Filter Parameters. SIU 2020: 1-4 - [c25]Ebru Yavuz, Önder Aydemir:
Classification of Mental Arithmetic Based Hybrid EEG+NIRS Signals. SIU 2020: 1-4
2010 – 2019
- 2018
- [c24]Hilal Altun, Ebru Ergün, Onder Aydemir:
Classification of electroencephalography signals recorded during olfaction of some spices. SIU 2018: 1-4 - [c23]Ebru Ergün, Onder Aydemir:
Classification of motor imaginary based Near-Infrared spectroscopy signals. SIU 2018: 1-4 - [c22]Bahar Hatipoglu, Cagatay Murat Yilmaz, Cemal Köse, Onder Aydemir:
Classification of wrist movements in different directions based on MEG signals. SIU 2018: 1-4 - 2017
- [j3]Onder Aydemir:
Olfactory Recognition Based on EEG Gamma-Band Activity. Neural Comput. 29(6): 1667-1680 (2017) - [c21]Zuzana Rost'áková, Georg Dorffner, Önder Aydemir, Roman Rosipal:
Estimation of Sleep Quality by Using Microstructure Profiles. AIME 2017: 105-115 - [c20]Onur Erdem Korkmaz, Onder Aydemir, Mehmet Öztürk:
Detection of smoking, gender and starvation - satiety using photoplethysmogram signals. SIU 2017: 1-4 - [c19]Hatice Okumus, Onder Aydemir:
Random forest classification for brain computer interface applications. SIU 2017: 1-4 - [c18]Ebru Yavuz, Onder Aydemir:
Determination of effective channels in brain-computer interface applications. SIU 2017: 1-4 - [c17]Onder Aydemir:
Combining sub-band power features extracted from different time segments of EEG trials. TSP 2017: 383-386 - [c16]Selin Aydin Fandakli, Onder Aydemir:
A fast and highly accurate EMG signal classification approach for multifunctional prosthetic fingers control. TSP 2017: 395-398 - [c15]Ebru Yavuz, Onder Aydemir:
Classification of EEG based BCI signals imagined hand closing and opening. TSP 2017: 425-428 - 2016
- [c14]Ebru Yavuz, Onder Aydemir:
Olfaction recognition by EEG analysis using wavelet transform features. INISTA 2016: 1-4 - [c13]Onder Aydemir:
Classification of electroencephalography signals recorded during smelling. SIU 2016: 1097-1100 - [c12]Onder Aydemir:
Classification of 2-dimensional cursor movement imagery EEG signals. TSP 2016: 370-373 - [c11]Onder Aydemir:
Classification of electroencephalography signals recorded during smelling of valerian and rosewater odors. TSP 2016: 392-395 - [c10]Kubra Saka, Onder Aydemir, Mehmet Öztürk:
Classification of EEG signals recorded during right/left hand movement imagery using Fast Walsh Hadamard Transform based features. TSP 2016: 413-416 - 2015
- [c9]Onder Aydemir:
Improving classification accuracy of EEG based brain computer interface signals. SIU 2015: 176-179 - [c8]Onder Aydemir:
Improving the effectiveness of common spatial pattern features at brain computer interface applications. SIU 2015: 351-354 - [c7]Onder Aydemir:
Detection of highly motivated time segments of motor imagery brain computer interface signals. SIU 2015: 743-746 - 2014
- [c6]Onder Aydemir, Temel Kayikçioglu:
Classification of electroencephalogram signals based on cursor movement imagery. SIU 2014: 858-861 - 2013
- [c5]Onder Aydemir, Temel Kayikçioglu:
Deciding the appropriate Mother Wavelet for extract features from brain computer interface signals. SIU 2013: 1-4 - [c4]Masoud Maleki, Kübra Eroglu, Onder Aydemir, Negin Manshoori, Temel Kayikçioglu:
A new method for selection optimum k value in k-NN classification algorithm. SIU 2013: 1-4 - 2012
- [j2]Onder Aydemir:
Letter to the Editor: Regarding ''Performance evaluation of multiple classifications of the ultrasonic supraspinatus images by using ML, RBFNN and SVM classifiers''. Expert Syst. Appl. 39(12): 11323 (2012) - [c3]Shahin Pourzare, Onder Aydemir, Temel Kayikçioglu:
Classification of EEG signals recorded during in facial movements for human-machine interaction. SIU 2012: 1-4 - [c2]Shahin Pourzare, Onder Aydemir, Temel Kayikçioglu:
Classification of various facial movement artifacts in EEG signals. TSP 2012: 529-533 - 2011
- [c1]Onder Aydemir, Mehmet Öztürk, Temel Kayikçioglu:
Performance evaluation of five classification algorithms in low-dimensional feature vectors extracted from EEG signals. TSP 2011: 403-407 - 2010
- [j1]Temel Kayikçioglu, Onder Aydemir:
A polynomial fitting and k-NN based approach for improving classification of motor imagery BCI data. Pattern Recognit. Lett. 31(11): 1207-1215 (2010)
Coauthor Index
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