Information Technology
Umair Qureshi
- Senior Lecturer, Information Technology
- umair.qureshi@jcu.edu.au
Chao Chen
- Adjunct Senior Lecturer
- chao.chen@jcu.edu.au
Dmitry Konovalov
- Senior Lecturer
- dmitry.konovalov@jcu.edu.au
Trina Myers
- Adjunct Professor
- trina.myers@my.jcu.edu.au
Iti Chaturvedi
- Lecturer, Information Technology
- iti.chaturvedi@jcu.edu.au
Euijoon Ahn
- Senior Lecturer, Information Technology
- euijoon.ahn@jcu.edu.au
Ickjai Lee
- Professor - Promotional Chair
- ickjai.lee@jcu.edu.au
Kyungmi Joanne Lee
- Senior Lecturer
- joanne.lee@jcu.edu.au
Kranthi Addanki
- Lecturer, Information Technology
- kranthi.addanki@jcu.edu.au
Lindsay Ward
- Senior Lecturer
- lindsay.ward@jcu.edu.au
An Artificial Intelligence Enabled Automatic Detection of Estuarine Crocodiles in Queensland Waterways Using Digital Video
This is a collaborative project between James Cook University (JCU) and the Department of Environment, Science, and Innovation (DESI) to develop an artificial intelligence (AI) based software that leverages digital video for the detection of estuarine crocodiles (C. Porosus) in Queensland's waterways. Building on previous research and utilizing extensive footage from Hartley’s Crocodile Adventures, this project aims to create an AI-based pilot detection system operational in both day and night settings to enhance safety around high-risk waterways.
Develop an autonomous AI vehicle damage assessment tool (Old ID 26683)
Development of a practical means and method for automated detection, identification and categorisation of vehicle panel damage using AI, deep learning and selected semantic segmentation networks. Semi-Supervised methods will be investigated to minimize the requirements on hand made training data (archived damaged vehicle images) and research will be conducted to determine the possibility to build a minimum viable product (MVP) directly onto the existing platform architecture.
Develop an autonomous AI vehicle damage assessment tool (Phase II) (Old ID 27223)
Improvement upon the project 1 developed method for automated detection, identification and categorisation of vehicle panel damage by developing a user interface and video vision. Semantic segmentation and deep learning networks will be further refined and developed for the next evolution/iteration of the software platform.
Higher order Voronoi diagrams for disaster and emergency management
- 2007
- University of Melbourne
- Researchers:Ickjai LeeKyungmi Joanne Lee
Start Date:
01 Jan 2002
End Date:
01 Jan 2003
Start Date:
01 Jan 2007
End Date:
01 Jan 2008
Start Date:
01 Jan 2024
End Date:
01 Jan 2026
Start Date:
01 Jan 2020
End Date:
01 Jan 2021
Start Date:
01 Jan 2020
Start Date:
01 Jan 2025
Start Date:
01 Jan 2020
Title:
JCU Open day
Title:
JCU Inspiration on Tap
Start Date:
01 Jan 2023
Start Date:
01 Jan 2017
