The classification of wink-based eeg signals by means of transfer learning models
Stroke is one of the dominant causes of impairme nt. An estimation of half post-stroke survivors suffer from a severe motor or cognitive deterioration, that affects the functionality of the affected parts of the body, which in turn, prevents the patients from carrying out Activities of Daily Living...
Автор: | Jothi Letchumy, Mahendra Kumar |
---|---|
Формат: | Дисертація |
Мова: | English |
Опубліковано: |
2021
|
Предмети: | |
Онлайн доступ: | http://umpir.ump.edu.my/id/eprint/34356/1/The%20classification%20of%20wink-based%20eeg.pdf |
Схожі ресурси
Схожі ресурси
-
The Classification of Wink-Based EEG Signals: The identification on efficiency of transfer learning models by means of kNN classifier
за авторством: Jothi Letchumy, Mahendra Kumar, та інші
Опубліковано: (2021) -
The classification of EEG-based winking signals: a transfer learning and random forest pipeline
за авторством: Jothi Letchumy, Mahendra Kumar, та інші
Опубліковано: (2021) -
The classification of EEG-based wink signals: A CWT-Transfer Learning pipeline
за авторством: Jothi Letchumy, Mahendra Kumar, та інші
Опубліковано: (2021) -
An evaluation of different fast fourier transform - transfer learning pipelines for the classification of wink-based EEG signals
за авторством: Jothi Letchumy, Mahendra Kumar, та інші
Опубліковано: (2020) -
The Classification of Wink-Based EEG Signals: The Identification of Significant Time-Domain Features
за авторством: Jothi Letchumy, Mahendra Kumar, та інші
Опубліковано: (2021)