Hyperspectral imaging is one of the rapidly growing domains in remote sensing primarily due to the breadth of applications on a variety of areas, from plant disease detection to object tracking. For example, hyperspectral imaging provides an opportunity to develop fast and non-invasive methods of detecting plant diseases and potentially discriminating between different disease types (e.g. virus, fungus, bacteria) before the human eye can see them. The principal aim of this PhD research program is to develop methods to improve the hyperspectral image classification using deep learning techniques. The developed systems will be evaluated on their ability to detect plant diseases and potentially discriminating between different disease types using the hyperspectral imaging dataset which has been already collected by CSIRO.
Eligibility
You must: meet QUT’s PhD admission criteria (Degree in Electrical Engineering and/or Computer Science with first class honours). We would like you to have: sound knowledge of machine learning, computer vision and image processing, strong programming skills.
Frequency
Annual
Student type
Australian and New Zealand
For Australian students
For international students
Level of study
Postgraduate
Field of studys
Computing and information technology Mathematics Sciences
