Hubert Cecotti
Hubert Cecotti
Associate Professor in Computer Science, California State University, Fresno
Verified email at - Homepage
Cited by
Cited by
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
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
Spelling with non-invasive Brain–Computer Interfaces–Current and future trends
H Cecotti
Journal of Physiology-Paris 105 (1-3), 106-114, 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
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
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
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
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
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
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
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
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
Grape detection with convolutional neural networks
H Cecotti, A Rivera, M Farhadloo, MA Pedroza
Expert Systems with Applications 159, 113588, 2020
A multimodal gaze-controlled virtual keyboard
H Cecotti
IEEE Transactions on Human-Machine Systems 46 (4), 601-606, 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
Cultural heritage in fully immersive virtual reality
H Cecotti
Virtual Worlds 1 (1), 82-102, 2022
Multiple stages of information processing are modulated during acute bouts of exercise
T Bullock, H Cecotti, B Giesbrecht
Neuroscience 307, 138-150, 2015
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
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
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
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