Deepfakes detection deals with machine learning methods, which detect if an image/video/audio sample is manipulated with a generative AI software. In recent years, deepfakes have been increasingly used for malicious purposes, including financial fraud, misinformation campaigns, identity theft, and cyber harassment. The ability to generate highly realistic synthetic content poses a serious threat to digital security, privacy, and trust in media. This project will develop methods for detecting deepfakes.
Honours and Masters project
Displaying 51 - 60 of 236 honours projects.
Primary supervisor: Hao Wang
The world’s energy markets are transforming, and more renewable energy is integrated into the electric energy market. The intermittent renewable supply leads to unexpected demand-supply mismatches and results in highly fluctuating energy prices. Energy arbitrage aims to strategically operate energy devices to leverage the temporal price spread to smooth out the price differences in the market, which also generates some revenue.
Primary supervisor: Kalin Stefanov
Computational modelling of sign languages aims to develop technologies that can serve as means for understanding (i.e., recognising) and producing (i.e., generating) a particular sign language. The objective of this project is to study and contribute to the state-of-the-art in sign language segmentation.
This is a research project best for students who are independent and willing to take up challenges. It is also a good practice for students who wish to pursue further study at a postgraduate level.
Primary supervisor: Sadia Nawaz
Project Description:
The project is focused on developing game-based learning environments where the users’ trace or interaction data could be collected. The game-based environment needs to be designed to allow the users to navigate and explore at their own pace. Using the environment, the participants can practice their technical/professional skills from various options.
Primary supervisor: Delvin Varghese
Mental health challenges disproportionately affect vulnerable populations, often due to limited access to traditional healthcare services. The rise of Generative AI offers a groundbreaking opportunity to bridge this gap by providing personalized, scalable, and accessible mental health support. This project, led out of Action Lab, aims to harness the potential of Generative AI to develop innovative technologies tailored for mental health interventions.
Primary supervisor: Kalin Stefanov
Computational modelling of sign languages aims to develop technologies that can serve as means for understanding (i.e., recognising) and producing (i.e., generating) a particular sign language. The objective of this project is to study and contribute to the state-of-the-art in sign language recognition.
This is a research project best for students who are independent and willing to take up challenges. It is also a good practice for students who wish to pursue further study at a postgraduate level.
Primary supervisor: Kalin Stefanov
Computational modelling of sign languages aims to develop technologies that can serve as means for understanding (i.e., recognising) and producing (i.e., generating) a particular sign language. The objective of this project is to study and contribute to the state-of-the-art in sign language generation.
This is a research project best for students who are independent and willing to take up challenges. It is also a good practice for students who wish to pursue further study at a postgraduate level.
Primary supervisor: Kalin Stefanov
Recognising conversational nonverbal behaviour for speakers and listeners, such as hand gestures, facial expressions and eye-gaze, is of great importance for natural interaction with intelligent agents. The objective of this project is to study and contribute to the state-of-the-art in conversational nonverbal behaviour recognition.
This is a research project best for students who are independent and willing to take up challenges. It is also a good practice for students who wish to pursue further study at a postgraduate level.
Primary supervisor: Kalin Stefanov
Generating conversational nonverbal behaviour for speakers and listeners, such as hand gestures, facial expressions and eye-gaze, is of great importance for natural interaction with intelligent agents. The objective of this project is to study and contribute to the state-of-the-art in conversational nonverbal behaviour generation.
This is a research project best for students who are independent and willing to take up challenges. It is also a good practice for students who wish to pursue further study at a postgraduate level.