Salihah Alotaibi

Effective modelling of conditional mutual information-guided feature reduction with multi-layer extreme learning machines enabled real-time human activity recognition for disabled people

Mathematical modelling of attention-guided deep learning for real-time text emotion recognition in assistive interaction systems for disabled persons.

This study introduces an Attention-Guided Deep Learning Framework for Real-Time Text Emotion Recognition for Individuals with Disabilities (AGDL-TERID) model. The AGDL-TERID model aims to enhance assistive human-computer interaction by accurately identifying emotions from textual inputs generated by users with disabili...

Advancing Alzheimer’s Disease Prediction with Optimized Deep and Active Learning Approaches

Alzheimer’s Disease (AD) is a progressive neurological disorder primarily affecting cognitive and memory functions. Artificial Intelligence (AI)-based early detection systems are needed to address the increasing incidence of AD. However, the traditional detection systems suffer from several challenges, including clas...

Hybrid Deep Neural Network with Natural Language Processing Techniques to Analyze Customer Satisfaction with Delivery Platform Manager Responses

This study presents a Hybrid Deep Neural Network Model for Customer Satisfaction Analysis (HDNNM-CSA), with the aim of developing an efficient model which is capable of accurately classifying customer satisfaction levels in delivery apps based on textual responses provided by customer experience managers.