Visual Intelligence Laboratory

Welcome to the Visual Intelligence Laboratory (VI-Lab) Webpage. My name is Thanapong Intharah. I am an assistant professor at the Department of Statistics, Khon Kaen University (KKU). I am the director of VI-Lab which works on applying Machine Learning and Computer Vision to solve real world problems. Many of our projects were spun off as commercialized products .

I did my PhD at UCL under supervision of Professor Gabriel Brostow. At UCL, I had been working on using Computer Vision to improve Programming by Demonstration, Learning to Automate GUI Tasks from Demonstration (project page). Before joining KKU, I have founded a Deep Tech startup, TinyEpicBrains, where we work on invisible QR code. Currently, I am interested in Computer Vision for 3D data, video data and applications of AI in Healthcare. I am also working on AI enhanced hardwares such as a differential dynamic microscopy and smart-glasses.

Thanapong Intharah, Ph.D.

Linkedin / Google Scholar

Visual domains such as Medical Imaging and Video Analysis are our expertise, but we also worked on Chatbot, NLP, and other Machine Learning domains. The following are list of selected research projects.

We proposed A DDM device that is enhanced by Deep Frame Interplation Networks.

We developed an AI to assist doctors and radiologists in diagnosing abnormalities in human upper abdominal through ultrasound image.

The OV-RDT platform consists of a mobile app, AI agents, and a dashboard. The mobile app captures and detects OV-RDT test kits via smartphone cameras. AI ensures image quality and identifies Opisthorchiasis presence and severity. Data, including AI diagnostics, are stored and displayed on a dashboard for analysis in epidemiology and patient screening progress.

Utilizing deep learning techniques, our project enhances dental care planning by accurately estimating age and gender from panoramic radiographs. Achieving 87.38% gender prediction accuracy and 1.96 years' age estimation error, it offers early diagnosis and forensic applications while ensuring model interpretability.

Valolyze: A Valorant gameplay analytics. Valolyze enables comprehensive analysis of Valorant gameplay from video recordings, empowering players and researchers alike in their quest for mastery and insights.

The KKU Herbarium Metaverse is a virtual simulation of the physical herbarium, offering a way to disseminate knowledge about plant diversity to a wider audience through an interactive platform that can display unlimited exhibition spaces and models of flowers regardless of the season, using photogrammetry techniques to create 3D models.

The development of a machine learning model for estimating the specific surface area (BET surface area) of carbon from plants using Scanning Electron Microscopy (SEM) images through deep learning is now available as a web application for predicting the BET surface area value, aiding in the use of renewable energy storage devices.

A system for determining human age from panoramic radiographs has been developed using deep learning techniques, resulting in a web application that is faster, more accurate, and reduces dental errors in diagnostic planning, dental and orthodontic treatment, and forensic identification.

We developed a web application that converts 3D models into voxel models with texture colors based on the color of the input models, for use in platforms such as game assets and non-fungible tokens (NFTs), providing the benefit of having voxel models with the same texture color as the input model.

We developed a web application for estimating car parts and their damage level using deep learning.

In this work, we propose dual image QR codes that aim to improve QR code capacity and appearance while preserving the ability to be able to scan by standard QR code readers.

This work focused on detecting prostate cancer lesions in MRI images where the size of the dataset is comparatively small.

In this work, we developed an end-to-end car damage estimation system via mobile camera. To estimate the damage, we first build 3D models of a car with images from a mobile camera and compared the model through CNN.

We proposed a new method to estimate shade of the denture with a mobile phone camera through the power of machine learning.

Tagging questions according to their topics is useful for internet forum management. In this work, we use the Bidirectional Encoder Representations from Transformers (BERT) model to categorize posts from Thai legal internet forums.

We applied Photogrammetry technique to build models of plastic tooth to help dental students pratice Prosthodontics.

We developed a dataset by scraping from YouTube and manually annotated them. We then train an AI to detect persons who concealed when they entered the scene.

We developed a chatbot to help associated medical science students learn about 7 medically important parasite eggs.

We developed a korean cover dance dataset and a pose evaluation technique to evaluate dance imitation score

Current
Thanapong Intharah, Ph.D.  Principal Investigator
Yupaporn Wanna  Research Assistant
Kannika Wiratchawa  Research Assistant
Pharamut Markjarun  Research Assistant
Natthanich Hirunchavarod  Research Assistant

Alumni
Yupaporn Wanna (BSc 2020),  Pimonpun Chachomphon (BSc 2020),  Sirirat Cha-in (BSc 2020),  Pakinee Kriamthaisong (BSc 2020),  Chanikan Phadungkit (BSc 2020),  Siriwan Thanachitboon (BSc 2020),  Thitiya Thanjai (BSc 2020),  Thepdumrong jaisue (BSc 2020),  Chunchila Sanguanram (BSc 2020),  Chadaporn Sontaikaew (BSc 2020),  Jarupa Buapa (BSc 2020),  Pannathon Sararat (BSc 2020),  Kannika Wiratchawa (BSc 2021),  Phornpirom Lojarat (BSc 2021),  Thachamin siangeung (BSc 2021),  Phattarawat Jaitiang (BSc 2021),  Nattharit Sawetwaranont (BSc 2021),  Jantraphon Somsuay (BSc 2021),  Mutita Butakhiaw (BSc 2021),  Kroravit Tharangsri (BSc 2022),  Thanapon Tayotee (BSc 2022),  Thanadol Chainet (BSc 2022),  Pharamut Markjarun (BSc 2022),  Waraporn Sittiwong (BSc 2022),  Rattaporn Leenaracharoongruang (BSc 2022),  Chakrit Kammason (MSc 2023),  Sitthatka Jarussang (BSc 2023),  Thanik Pimpiban (BSc 2023),  Kittikhun Kiattisaksiri (BSc 2023),  Chayakon Chanlun (BSc 2023),  Wanita Somdej (BSc 2023),  Athitiya Thamavongsa (BSc 2023),  Jittakorn Chanthasi (BSc 2023),  Naruemon Saisophon (BSc 2023),  Supidchaya Tangkidwanich (BSc 2023),  Umaporn Kamphichai (BSc 2023),  Nutsuda Penpong (MSc 2023),  Nattakon Puangkaew (BSc 2024),  Thanapat Sopon (BSc 2024),  Natthanich Hirunchavarod (BSc 2024),  Pornnakanok Phuphatham (BSc 2024),  Narawit Prathansap (BSc 2024), Yupaporn Wanna (MSc 2024)  .....