Project Details
Overview
SECaM PhD Studentship, University Research Studentship (URS) fund General.
A PhD project investigating how quantum computing algorithms can be used in computer vision to detect falls. Falls frequently occur in the elderly community and can impact the lives of those who experience them. The ability to detect falls in real-time can potentially mitigate such consequences. Neural networks have been designed for pose estimation and fall detection, however they can struggle to perform optimally in real-time. Quantum computing has demonstrated potential within hybrid quantum-classical neural networks to improve model performance using fewer computational resources.
A PhD project investigating how quantum computing algorithms can be used in computer vision to detect falls. Falls frequently occur in the elderly community and can impact the lives of those who experience them. The ability to detect falls in real-time can potentially mitigate such consequences. Neural networks have been designed for pose estimation and fall detection, however they can struggle to perform optimally in real-time. Quantum computing has demonstrated potential within hybrid quantum-classical neural networks to improve model performance using fewer computational resources.
Project Aims
The primary aim is to develop a real-time quantum computing-assisted fall detection system. To reach this milestone, a real-time quantum computing-assisted pose estimator will be the basis of such a fall detection system.
| Status | Active |
|---|---|
| Effective start/end date | 1/10/24 → 30/09/27 |