[PDF][PDF] Brain stroke computed tomography images analysis using image processing: A review

NH Ali, AR Abdullah, NM Saad, AS Muda… - Int J Artif Intell …, 2021 - researchgate.net
Brain is a hugely complex and fascinating organ in the human body composing of cerebrum,
cerebellum, and brainstem that being protected by the skull [1]. This organ is composed of a …

Simplified Prediction Method for Detecting the Emergency Braking Intention Using EEG and a CNN Trained with a 2D Matrices Tensor Arrangement

HJ Mora, EJ Pino - International Journal of Human–Computer …, 2023 - Taylor & Francis
The driver's mental state is frequently detected employing EEG signals which are usually
converted into grayscale images to train a Machine Learning algorithm that classifies his …

Implementation of an automatic EEG feature extraction with gated recurrent neural network for emotion recognition

RR Immanuel, SKB Sangeetha - … for SDGs: Select Proceedings of ICRTAC …, 2023 - Springer
Emotion is a complicated state that influences one's thoughts and behaviour. Recognizing
the emotions of a human being is a major research interest in the affective computing after …

User behavior data analysis and product design optimization algorithm based on deep learning

L Liang, Y Ke - International Journal on Interactive Design and …, 2023 - Springer
In modern society, user behavior data analysis and product design optimization have
become one of the key factors for the success of enterprises. Traditional methods are usually …

[PDF][PDF] A modified residual network for detection and classification of Alzheimer's disease

FS Hanoon, AHH Alasadi - International Journal of Electrical and …, 2022 - academia.edu
Alzheimer's disease (AD) is a brain disease that significantly declines a person's ability to
remember and behave normally. By applying several approaches to distinguish between …

[PDF][PDF] A survey on bio-signal analysis for human-robot interaction

HM Radha, AKA Hassan - International Journal of Electrical and …, 2022 - core.ac.uk
The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an
urgent demand for it in various applications, including health care, rehabilitation, research …

[PDF][PDF] Epileptic seizure classification of electroencephalogram signals using extreme gradient boosting classifier

M Panigrahi, DK Behera, KC Patra - Indonesian Journal of Electrical …, 2022 - academia.edu
Epilepsy causes repeated seizures in an individual's life, which causes transient
irregularities in the brain's electrical activity. It results in different physical symptoms that are …

A hybrid capsule attention-based convolutional bi-GRU method for multi-class mental task classification based brain-computer Interface

D Deepika, G Rekha - Computer Methods in Biomechanics and …, 2025 - Taylor & Francis
Electroencephalography analysis is critical for brain computer interface research. The
primary goal of brain–computer interface is to establish communication between impaired …

Classification of EEG signal by using optimized Quantum Neural Network

DS Abdul-Zahra, AT Jawad… - … Journal of Electrical …, 2021 - section.iaesonline.com
In recent years the algorithms of machine learning was used for brain signals identifing
which is a useful technique for diagnosing diseases like Alzheimer's and epilepsy. In this …

Deep Learning Approach for Classification of Alzheimer's Disease

AHH Alasadi, FS Hanoon - Intelligent Internet of Things for Smart …, 2023 - taylorfrancis.com
Alzheimer's is a brain disease in which the ability to think, remember, and behave
significantly decreases. Using different approaches and algorithms to distinguish between …