Domain adaptation and transfer learning methods enhance deep learning models used in inner speech based brain computer interfaces

Mostrar todas las versiones(2)

Brain-Computer Interfaces are useful devices that can partially restore communication from severely compromised patients. Although advances in deep learning have significantly improved brain pattern recognition, a large amount of data is required for training these deep architectures. In recent year...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Zablocki, Luciano Ivan, Mendoza, Agustín Nicolás, Nieto, Nicolás
Formato: Articulo
Lenguaje:Inglés
Publicado: 2023
Materias:
Ciencias Informáticas
Deep Learning
Domain Adaptation
Transfer Learning
Convolutional Neural Network
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/156752
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-156752
record_format dspace
spelling I19-R120-10915-1567522023-08-23T20:04:35Z http://sedici.unlp.edu.ar/handle/10915/156752 Domain adaptation and transfer learning methods enhance deep learning models used in inner speech based brain computer interfaces Zablocki, Luciano Ivan Mendoza, Agustín Nicolás Nieto, Nicolás 2023-05 2023-08-23T18:09:38Z en Ciencias Informáticas Deep Learning Domain Adaptation Transfer Learning Convolutional Neural Network Brain-Computer Interfaces are useful devices that can partially restore communication from severely compromised patients. Although advances in deep learning have significantly improved brain pattern recognition, a large amount of data is required for training these deep architectures. In recent years, the inner speech paradigm has drawn much attention, as it can potentially allow natural control of different devices. However, as of the date of this publication, there is only a small amount of data available in this paradigm. In this work we show that it is possible, through transfer learning and domain adaptation methods, to make the most of the scarce data, enhancing the training process of a deep learning architecture used in brain-computer interfaces. Sociedad Argentina de Informática e Investigación Operativa Articulo Articulo http://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) application/pdf 67-81
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Deep Learning
Domain Adaptation
Transfer Learning
Convolutional Neural Network
spellingShingle Ciencias Informáticas
Deep Learning
Domain Adaptation
Transfer Learning
Convolutional Neural Network
Zablocki, Luciano Ivan
Mendoza, Agustín Nicolás
Nieto, Nicolás
Domain adaptation and transfer learning methods enhance deep learning models used in inner speech based brain computer interfaces
topic_facet Ciencias Informáticas
Deep Learning
Domain Adaptation
Transfer Learning
Convolutional Neural Network
description Brain-Computer Interfaces are useful devices that can partially restore communication from severely compromised patients. Although advances in deep learning have significantly improved brain pattern recognition, a large amount of data is required for training these deep architectures. In recent years, the inner speech paradigm has drawn much attention, as it can potentially allow natural control of different devices. However, as of the date of this publication, there is only a small amount of data available in this paradigm. In this work we show that it is possible, through transfer learning and domain adaptation methods, to make the most of the scarce data, enhancing the training process of a deep learning architecture used in brain-computer interfaces.
format Articulo
Articulo
author Zablocki, Luciano Ivan
Mendoza, Agustín Nicolás
Nieto, Nicolás
author_facet Zablocki, Luciano Ivan
Mendoza, Agustín Nicolás
Nieto, Nicolás
author_sort Zablocki, Luciano Ivan
title Domain adaptation and transfer learning methods enhance deep learning models used in inner speech based brain computer interfaces
title_short Domain adaptation and transfer learning methods enhance deep learning models used in inner speech based brain computer interfaces
title_full Domain adaptation and transfer learning methods enhance deep learning models used in inner speech based brain computer interfaces
title_fullStr Domain adaptation and transfer learning methods enhance deep learning models used in inner speech based brain computer interfaces
title_full_unstemmed Domain adaptation and transfer learning methods enhance deep learning models used in inner speech based brain computer interfaces
title_sort domain adaptation and transfer learning methods enhance deep learning models used in inner speech based brain computer interfaces
publishDate 2023
url http://sedici.unlp.edu.ar/handle/10915/156752
work_keys_str_mv AT zablockilucianoivan domainadaptationandtransferlearningmethodsenhancedeeplearningmodelsusedininnerspeechbasedbraincomputerinterfaces
AT mendozaagustinnicolas domainadaptationandtransferlearningmethodsenhancedeeplearningmodelsusedininnerspeechbasedbraincomputerinterfaces
AT nietonicolas domainadaptationandtransferlearningmethodsenhancedeeplearningmodelsusedininnerspeechbasedbraincomputerinterfaces
_version_ 1807221078714482688

Ejemplares similares