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Electrical and Electronics Commons™

Open Access. Powered by Scholars. Published by Universities.®

2022

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Articles 241 - 243 of 243

Full-Text Articles in Electrical and Electronics

Online Self-Learning System For Prediabetes Patients, Ye Moe Myint Jan 2022

Online Self-Learning System For Prediabetes Patients, Ye Moe Myint

Chulalongkorn University Theses and Dissertations (Chula ETD)

This thesis implements a web-based application that combines a 3D learning center and educational game to facilitate the monitoring, management, and treatment of patients with prediabetes mellitus, by providing exercise plans and controlled diets. The application utilizes advanced web technologies, 3D modeling, and gamification principles to create an engaging learning experience. User-centered design ensures usability, and testing demonstrates positive outcomes, including increased knowledge, motivation, and engagement. This research contributes to digital health interventions by empowering prediabetes patients with informed decision-making and healthy habits. Future directions include expanding the application, refining the user interface, and evaluating long-term impact on prediabetes management.

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Deep Iterative Convolutional Neural Network For Face Image Super-Resolution, Hein Htet Aung Jan 2022

Deep Iterative Convolutional Neural Network For Face Image Super-Resolution, Hein Htet Aung

Chulalongkorn University Theses and Dissertations (Chula ETD)

Face images are often used today for many purposes, including facial identification and recognition. Face identification is used in security to trace crimes. The face application performs poorly due to the camera's low quality and environmental degradation issues. In this thesis, we explore face image super-resolution, which raises low-resolution to high resolution images. We proposed a deep iterative convolutional neural network using attention mechanisms and spatial feature transformation for face super-resolution. The input low-resolution image is enlarged into a super-resolution face image. Then, the image has repeatedly estimated the alignment to enhance the super-resolution image. The experiment was conducted on …

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Diabetic Retinopathy Severity Classification Using Convolutional Neural Network Withtransfer Learning, Pranajit Kumar Das Jan 2022

Diabetic Retinopathy Severity Classification Using Convolutional Neural Network Withtransfer Learning, Pranajit Kumar Das

Chulalongkorn University Theses and Dissertations (Chula ETD)

Diabetic Retinopathy is a common retina disease caused by diabetes that is very difficult to diagnose initially because of its asymptomatic nature, which leads to permanent vision loss. Early and accurate detection of diabetic retinopathy is an effective way to prevent blindness. While screening programs are the most effective means of detecting diabetic retinopathy, it has various limitations like time consuming, laborious tasks, require a lot of expert ophthalmologists and technicians with standardized medical equipment. Automatic diabetic retinopathy classification using artificial intelligence and computer vision techniques mostly overcome the above-mentioned limitations despite it still being a challenging task. In this …

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