Hubert Cecotti 个人学术档案

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Girijesh PrasadProfessor of Intelligent Systems, University of Ulster, Magee Campus在 ulster.ac.uk 的电子邮件经过验证
Yogesh Kumar MeenaAssistant Professor, IIT Gandhinagar在 iitgn.ac.in 的电子邮件经过验证
Barry GiesbrechtPsychological & Brain Sciences, UC Santa Barbara在 ucsb.edu 的电子邮件经过验证
Haider RazaSenior Lecturer in Artificial Intelligence, University of Essex在 essex.ac.uk 的电子邮件经过验证
Dheeraj RatheeAI Data Scientist, Provide CIC, University of Essex, UK在 essex.ac.uk 的电子邮件经过验证
Manu MabyResearch engineer Inserm, Lyon Neuroscience Research Center在 inserm.fr 的电子邮件经过验证
Jérémie MattoutLyon Neuroscience Research Center在 inserm.fr 的电子邮件经过验证
Ivan VolosyakProfessor für Biomedical Engineering在 hochschule-rhein-waal.de 的电子邮件经过验证
Miguel EcksteinProfessor of Psychological and Brain Sciences, University of California, Santa Barbara在 psych.ucsb.edu 的电子邮件经过验证
Abdel BelaidProfessor of Computer Science在 loria.fr 的电子邮件经过验证
Marco CongedoCNRS (French National Centre for Scientific Research), Grenoble Alpes University, Grenoble INP在 gipsa-lab.grenoble-inp.fr 的电子邮件经过验证
Yuhua LiCardiff University在 cardiff.ac.uk 的电子邮件经过验证
Szilard VAJDACentral Washington University在 cwu.edu 的电子邮件经过验证
Christian JuttenEmeritus Prof. of Statistical Signal Processing, Univ. Grenoble Alpes, Institut Universitaire de在 gipsa-lab.fr 的电子邮件经过验证
Ashish DuttaProfessor of Mechanical Engineering, IIT Kanpur在 iitk.ac.in 的电子邮件经过验证
Michael Callaghanuniversity of ulster在 ulster.ac.uk 的电子邮件经过验证
Jonathan (Jon) TouryanU.S. Army Research Laboratory在 mail.mil 的电子邮件经过验证
Professor Damien CoyleThe Bath Institute for the Augmented Human, University of Bath在 bath.ac.uk 的电子邮件经过验证
Amar MaratheArmy Research Laboratory在 case.edu 的电子邮件经过验证
Tom BullockUC Santa Barbara在 psych.ucsb.edu 的电子邮件经过验证

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Hubert Cecotti

Associate Professor in Computer Science, California State University, Fresno

在 csufresno.edu 的电子邮件经过验证 - 首页

pattern recognition machine learning brain-computer interface neural networks virtual reality


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces H Cecotti, A Gräser IEEE Transactions on Pattern Analysis and Machine Intelligence, 0	905*
A self-paced and calibration-less SSVEP-based brain–computer interface speller H Cecotti IEEE transactions on neural systems and rehabilitation engineering 18 (2 …, 2010	311	2010
Spelling with non-invasive Brain–Computer Interfaces–Current and future trends H Cecotti Journal of Physiology-Paris 105 (1-3), 106-114, 2011	210	2011
Convolutional neural network with embedded Fourier transform for EEG classification H Cecotti, A Graeser 2008 19th International Conference on Pattern Recognition, 1-4, 2008	152	2008
Single-trial classification of event-related potentials in rapid serial visual presentation tasks using supervised spatial filtering H Cecotti, MP Eckstein, B Giesbrecht IEEE transactions on neural networks and learning systems 25 (11), 2030-2042, 2014	127	2014
Adaptive learning with covariate shift-detection for motor imagery-based brain–computer interface H Raza, H Cecotti, Y Li, G Prasad Soft Computing 20, 3085-3096, 2016	126	2016
A review of rapid serial visual presentation-based brain–computer interfaces S Lees, N Dayan, H Cecotti, P McCullagh, L Maguire, F Lotte, D Coyle Journal of neural engineering 15 (2), 021001, 2018	120	2018
A robust sensor-selection method for P300 brain–computer interfaces H Cecotti, B Rivet, M Congedo, C Jutten, O Bertrand, E Maby, J Mattout Journal of neural engineering 8 (1), 016001, 2011	120	2011
Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface H Raza, D Rathee, SM Zhou, H Cecotti, G Prasad Neurocomputing 343, 154-166, 2019	100	2019
Evaluation of the Bremen SSVEP based BCI in real world conditions I Volosyak, H Cecotti, D Valbuena, A Graser 2009 IEEE International Conference on Rehabilitation Robotics, 322-331, 2009	96	2009
Grape detection with convolutional neural networks H Cecotti, A Rivera, M Farhadloo, MA Pedroza Expert Systems with Applications 159, 113588, 2020	81	2020
A time–frequency convolutional neural network for the offline classification of steady-state visual evoked potential responses H Cecotti Pattern Recognition Letters 32 (8), 1145-1153, 2011	81	2011
Impact of frequency selection on LCD screens for SSVEP based brain-computer interfaces I Volosyak, H Cecotti, A Gräser Bio-Inspired Systems: Computational and Ambient Intelligence: 10th …, 2009	81	2009
A multimodal gaze-controlled virtual keyboard H Cecotti IEEE Transactions on Human-Machine Systems 46 (4), 601-606, 2016	73	2016
Reliable visual stimuli on LCD screens for SSVEP based BCI H Cecotti, I Volosyak, A Gräser 2010 18th European Signal Processing Conference, 919-923, 2010	67	2010
Cultural heritage in fully immersive virtual reality H Cecotti Virtual worlds 1 (1), 82-102, 2022	62	2022
Multiple stages of information processing are modulated during acute bouts of exercise T Bullock, H Cecotti, B Giesbrecht Neuroscience 307, 138-150, 2015	57	2015
Best practice for single-trial detection of event-related potentials: Application to brain-computer interfaces H Cecotti, AJ Ries International Journal of Psychophysiology 111, 156-169, 2017	54	2017
Optimal visual stimuli on LCD screens for SSVEP based brain-computer interfaces I Volosyak, H Cecotti, A Graser 2009 4th International IEEE/EMBS Conference on Neural Engineering, 447-450, 2009	54	2009
Theoretical analysis of xDAWN algorithm: application to an efficient sensor selection in a P300 BCI B Rivet, H Cecotti, A Souloumiac, E Maby, J Mattout 2011 19th European Signal Processing Conference, 1382-1386, 2011	48	2011

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