[HTML][HTML] Automated diagnosis of diabetic retinopathy using deep learning: On the search of segmented retinal blood vessel images for better performance
Diabetic retinopathy is one of the most significant retinal diseases that can lead to blindness.
As a result, it is critical to receive a prompt diagnosis of the disease. Manual screening can …
As a result, it is critical to receive a prompt diagnosis of the disease. Manual screening can …
Development of an EEG controlled wheelchair using color stimuli: A machine learning based approach
Brain-computer interface (BCI) has extensively been used for rehabilitation purposes. Being
in the research phase, the brainwave based wheelchair controlled systems suffer from …
in the research phase, the brainwave based wheelchair controlled systems suffer from …
Diagnosis of tobacco addiction using medical signal: An EEG-based time-frequency domain analysis using machine learning
Addiction such as tobacco smoking affects the human brain and thus causes significant
changes in the brainwaves. The changes in brain wave due to smoking can be identified by …
changes in the brainwaves. The changes in brain wave due to smoking can be identified by …
Classification Accuracy of Deep Learning in SSVEP Using Smart Glasses and LCD
W Nemoto, N Kobayashi - 2023 International Symposium on …, 2023 - ieeexplore.ieee.org
Brain-computer interface (BCI) is a tool that enables direct communication with a computer
using neural activity as a control signal. The most widely known electroencephalograms …
using neural activity as a control signal. The most widely known electroencephalograms …
EEG based Smart Wheelchair using Raspberry Pi for Elderly and Paralysed Patients
R Shashidhar, SS Tippannavar - 2022 IEEE 2nd Mysore Sub …, 2022 - ieeexplore.ieee.org
As a responsible citizen of the community, one should improve the standard of living for
people with disabilities. The disabled person faces a variety of issues, depending on the …
people with disabilities. The disabled person faces a variety of issues, depending on the …
RETRACTED: Fractal based feature extraction technique for classifying EEG signal for color visualization tasks
Exploring and finding Significant features for colour visualization tasks using the EEG
signals is crucial in developing a robust Brain-machine Interface (BMI). The visually evoked …
signals is crucial in developing a robust Brain-machine Interface (BMI). The visually evoked …
English Character recognition using EEG-based Visual stimulations: A Machine Learning Analysis
The development of Brain Computer Interfaces (BCI) using electroencephalography (EEG)
signals in e-learning systems for disabled people has received much interest from …
signals in e-learning systems for disabled people has received much interest from …
Subject-Independent P300 Speller Classification using Time-Frequency Representation and Double Input CNN with Feature Concatenation
Z Ermaganbet, A Mussabayeva… - … on Digital Signal …, 2023 - ieeexplore.ieee.org
This study proposes a Double Input Convolutional Neural Network with Feature
Concatenation (DiCNN-FC) for the classification task of the P300 speller. Two time …
Concatenation (DiCNN-FC) for the classification task of the P300 speller. Two time …
Event-Related Spectrogram Representation of EEG for CNN-Based P300 Speller
A Mussabayeva, Z Ermaganbet… - 2021 Asia-Pacific …, 2021 - ieeexplore.ieee.org
P300 speller is one of the most popular applications for electroencephalography (EEG)
features extraction and classification. It is used for enabling paralyzed people to …
features extraction and classification. It is used for enabling paralyzed people to …
[PDF][PDF] Brain tumor detection using step-constant tapered slot antenna by machine learning
A novel methodology to analyze performance of a Step-Constant tapered slot antenna
(STSA) for brain tumor detection by using machine learning is presented in this work. The …
(STSA) for brain tumor detection by using machine learning is presented in this work. The …