[HTML][HTML] Multi-class sentiment classification on Bengali social media comments using machine learning
Abstract Multi-class Sentiment Analysis (SA) is an important field of computational linguistics
that extracts multiple opinions expressed in a text using NLP and text-mining techniques …
that extracts multiple opinions expressed in a text using NLP and text-mining techniques …
EEG based brain computer interface for controlling a robot arm movement through thought
R Bousseta, I El Ouakouak, M Gharbi, F Regragui - Irbm, 2018 - Elsevier
Abstract Background The Brain Computer Interfaces (BCI) are devices allowing direct
communication between the brain of a user and a machine. This technology can be used by …
communication between the brain of a user and a machine. This technology can be used by …
The face detection/recognition, perspective and obstacles in robotic: a review
NMI Uddin, AJ Moshayedi… - … Endorsed Transactions on …, 2022 - publications.eai.eu
Facial recognition research is one of the different types of research in this world today. In
recent years, facial recognition in robots has attracted increased study interest. Robotic …
recent years, facial recognition in robots has attracted increased study interest. Robotic …
Calibrating EEG features in motor imagery classification tasks with a small amount of current data using multisource fusion transfer learning
Y Liang, Y Ma - Biomedical Signal Processing and Control, 2020 - Elsevier
Background and objective The identification of motor intention by analyzing
electroencephalogram (EEG) signals has become an important issue in brain-computer …
electroencephalogram (EEG) signals has become an important issue in brain-computer …
A novel P300 classification algorithm based on a principal component analysis-convolutional neural network
F Li, X Li, F Wang, D Zhang, Y Xia, F He - Applied sciences, 2020 - mdpi.com
Aiming at enhancing the classification accuracy of P300 Electroencephalogram signals in a
non-invasive brain–computer interface system, a novel P300 electroencephalogram signals …
non-invasive brain–computer interface system, a novel P300 electroencephalogram signals …
An efficient P300 detection algorithm based on kernel principal component analysis-support vector machine
Human-machine interaction using brain signals has been made possible by the advent of a
technology popularly known as a brain-computer interface (BCI). P300 is the most studied …
technology popularly known as a brain-computer interface (BCI). P300 is the most studied …
EEG efficient classification of imagined hand movement using RBF kernel SVM
R Bousseta, S Tayeb, I El Ouakouak… - 2016 11th …, 2016 - ieeexplore.ieee.org
Brain-machine interface (BMI) is a system that allows a person to control a device such as a
robot arm using only his or her brain activity. This work is aimed at discriminating between …
robot arm using only his or her brain activity. This work is aimed at discriminating between …
Robust subject-independent P300 waveform classification via signal pre-processing and deep learning
R Sahay, CG Brinton - IEEE Access, 2021 - ieeexplore.ieee.org
Brain Computer Interfaces (BCIs) are capable of processing neural stimuli using
electroencephalogram (EEG) measurements to aid communication capabilities. Yet, BCIs …
electroencephalogram (EEG) measurements to aid communication capabilities. Yet, BCIs …
Use of the stockwell transform in the detection of P300 evoked potentials with low-cost brain sensors
The evoked potential is a neuronal activity that originates when a stimulus is presented. To
achieve its detection, various techniques of brain signal processing can be used. One of the …
achieve its detection, various techniques of brain signal processing can be used. One of the …
Increasing the classification accuracy of EEG based brain-computer interface signals
G Dimitrov, P Petrov, I Dimitrova… - 2020 10th …, 2020 - ieeexplore.ieee.org
In the recent years the attention to Brain-Computer Interface (BCI) devices and their potential
for decoding human brain signals have risen considerably. The achieved results find …
for decoding human brain signals have risen considerably. The achieved results find …