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Found 15 matching student topics

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Controlling a surgical robot using visual feedback

Performing surgery is a difficult task that pushes surgeons to their mental and physical limits.Automation has been able to successfully reduce the burden on human workers in other industries (e.g. manufacturing) and is expected to be able to do the same for surgeons.Surgical robots are different from most industrial robots as they must be made in a way that makes them able to safely interact with a patient during surgery, which means that the typical methods of automation cannot be …

Study level
Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Creation and testing of computer-generated faces for cognitive experiments

The way humans perceive faces is an important factor in social systems. The shape and features of a person’s face help us predict the types of personality traits a person might have.Artificial faces can be generated with features that prompt certain judgements such as trust, dominance and attractiveness. However, the images traditionally used in studies that investigate these effects are quite outdated and would benefit from being updated based on the current improvements in computer generated imaging.This project provides the …

Study level
Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Information Systems

Next generation 3D imaging for diabetic footcare

This project is for strong students undertaking their group capstone project. It is expected that you will be working in a small team to explore and develop 3D imaging techniques for diabetic footcare by patients. This project is part of an engagement grant collaboration with CHI, podiatry, augmented reality and computer vision researchers.

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Autonomous UAV wildlife tracking using thermal imaging

The tracking of wildlife has been a key part of environmentalists and farmers work for many years. This project’s goal is to make tracking and locating animals a faster, simpler and more efficient process.This will be accomplished by automating the process through the use of Unmanned Arial Vehicles (UAVs). This research will explore the area of computer vision and its ability to pinpoint the location of wildlife and display them on a map for the convenience of the user.Watch the …

Study level
PhD, Master of Philosophy, Honours
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Universal feature detectors for image analysis

Computer vision techniques can now identiy complex objects from images using complicated neural networks that are trained from a large database. Often these networks learn to recognise geometric objects as part of its training.This project will investigate the creation of fast universal geometrical detectors (e.g. lines) to investigate whether they can improve speed and performance for complex computer vision tasks. …

Study level
Master of Philosophy, Honours
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Computer vision and machine learning for wildlife abundance estimation

Wildlife surveys are a key tool used to manage threatened and endangered species. Historically, these have been performed manually, however a growing number of surveys are using drones and automated detection techniques to both reduce the cost and improve the overall accuracy. For this to be effective, the species of interest needs to be reliably detected in the target footage, and needs to be tracked to ensure that each animal is only counted once. QUT has already developed an approach …

Study level
Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Scene understanding and reliable deep learning for robotics

For many practical applications of robotics and embodied AI, such as driverless cars, healthcare and domestic service robotics, scene understanding is a critical component. Modern methods rely heavily on deep learning to extract information about the scene from camera images.

Study level
Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Advanced vascular models for surgical education, training and diagnosis

Vascular surgery is Australia’s second-most expensive surgical program, primarily due to an aging population with increased incidence of cardiovascular disease, representing 29% of all deaths in 2017.Surgical decision-making regarding whether, when and how to operate on a patient relies on the clinicians’ analysis of 2D and 3D reconstructed images on a computer screen in either the endovascular suite or the operating room.Further, endovascular surgeries require skillful and rapid deployment of vascular prosthetics through tortuous, patient-specific geometries to safety, effectively and …

Study level
Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Chemistry, Physics and Mechanical Engineering

Robust pose estimation of objects using TensorFlow computation

Robust pose estimation of objects is needed for robotic application and human computer interfaces. Like most computer vision tasks, robust pose estimation becomes a challenging problem when the environmental conditions (like lighting and visibility) are not controlled.The approach we propose is to leverage the computational graphs that can be created in deep learning framework like TensorFlow. This approach opens up several strategies.For example, if a model of an object is available, a deep neural network can be trained to make …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Induction of object models from videos

For a number of practical applications, it is desirable to have 3D models of the objects of interest. For example, if you wanted to have a custom shoe made, an app that takes a video of you foot and create a precise 3D model would make the process easier.Another scenario is the modelling of non-rigid objects. For example, if we could induce from underwater videos of manta rays a 3D parameterized model of this species, the model would help in …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Machine learning using light fields for depth field generation

Light field cameras are cameras that capture both the angular and spatial information of rays in a scene in a single shot. This means that the light field can be used to calculate depth information of a scene. Current state-of-the-art light field depth calculation techniques are slow and computationally expensive and so are not suitable for most robotics applications. Machine learning approaches have been used in many areas of computer vision to increase the speed and robustness of various algorithms …

Study level
Master of Philosophy, Honours
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Weeds scouting in broadacre farms in the fallow period.

Weeds are becoming herbicides resistant which calls for alternative ways to target them, for example the use of microwaves or lasers. This requires the ability to detect individual weeds and plants, recognise its species and then select the best method for treating it.

Study level
Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

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