(Ben) THON Pun Liang
I hold a Master of Science (Research) from Swinburne University of Technology Sarawak (2024), where
I specialized in Explainable Artificial Intelligence (XAI) and Deep Learning for Medical Image
Analysis.
Currently, I work as a Data Scientist / AI Engineer in the Semiconductor Industry, focusing on
anomaly detection, virtual metrology, and workflow automation.
I earned my Bachelor of Computer Science (Data Science) from the same university in 2021.
plthon [at] outlook [dot] com  / 
LinkedIn  / 
GitHub  / 
Google Scholar / 
Résumé
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Investigation of ConViT on COVID-19 Lung Image Classification and the Effects of Image Resolution
and
Number of Attention Heads
Pun Liang Thon,
Joel C. M. Than,
Norliza M. Noor,
Jun Han,
Patrick Then
IJIE, 2023
fullpaper
Convolutional Vision Transformer (ConViT) achieves high accuracy and improved performance in
diagnosing
COVID-19 cases from lung CT scan images, offering a valuable complement to RT-PCR tests.
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Explainable COVID-19 Three Classes Severity Classification Using Chest X-Ray Images
Pun Liang Thon,
Joel C. M. Than,
Rosminah M. Kassim,
Ashari Yunus,
Norliza M. Noor,
Patrick Then
IECBES, 2022
fullpaper
This study explores the application of vision transformers for COVID-19 severity classification
using
CXR images, achieving an accuracy of 0.862 and utilizing Grad-CAM for interpretability.
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Preliminary Study on Patch Sizes in Vision Transformers (ViT) for COVID-19 and Diseased Lungs
Classification
Joel C. M. Than,
Pun Liang Thon,
Omar Mohd Rijal,
Rosminah M. Kassim,
Ashari Yunus,
Norliza M. Noor,
Patrick Then
NBEC, 2021
fullpaper
This study investigates the potential of Vision Transformers (ViT) for classifying COVID-19 and
normal
lung images, achieving a promising peak accuracy of 95.36% across diverse datasets and patch sizes.
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