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المصدر: EUSIPCO
Dose, H, Møller, J S, Puthusserypady, S & Iversen, H K 2018, A Deep Learning MI-EEG Classification Model for BCIs . in Proceedings of 2018 26th European Signal Processing Conference . IEEE, pp. 1690-93, 26th European Signal Processing Conference, Rome, Italy, 03/09/2018 . https://doi.org/10.23919/EUSIPCO.2018.8553332Testمصطلحات موضوعية: medicine.diagnostic_test, Computer science, business.industry, Deep learning, 0206 medical engineering, Feature extraction, Pattern recognition, 02 engineering and technology, Electroencephalography, 020601 biomedical engineering, Convolutional neural network, 03 medical and health sciences, 0302 clinical medicine, Motor imagery, medicine, Artificial intelligence, business, Classifier (UML), 030217 neurology & neurosurgery
وصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2cdafd91c986750796b585b8af431daTest
https://doi.org/10.23919/eusipco.2018.8553332Test -
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المؤلفون: Michael Hersche, Tino Rellstab, Pasquale Davide Schiavone, Lukas Cavigelli, Luca Benini, Abbas Rahimi
المصدر: 2018 26th European Signal Processing Conference (EUSIPCO)
مصطلحات موضوعية: Signal Processing (eess.SP), SVM, 0206 medical engineering, 02 engineering and technology, EEG, Motor imagery, Brain-computer interfaces, Multiclass classification, Multiscale features, 020601 biomedical engineering, 03 medical and health sciences, ComputingMethodologies_PATTERNRECOGNITION, 0302 clinical medicine, FOS: Biological sciences, Quantitative Biology - Neurons and Cognition, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Neurons and Cognition (q-bio.NC), 020201 artificial intelligence & image processing, Electrical Engineering and Systems Science - Signal Processing, 030217 neurology & neurosurgery
وصف الملف: application/application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e75a716eeb3e9017f8a86d51b2224ae4Test
https://doi.org/10.23919/eusipco.2018.8553378Test