Research
Current research focuses on pose estimation with applications to spacecraft
and robot navigation. Other interest includes image
machine learning and deep learning,
image classification, object localisation/recognition,
image features, image saliency, and image segmentation.
Research interest topics are listed as follows,
- Computer Vision
- Deep Learning Car Detection Comparison
- AI Edge Computing Devices Demonstration
- PhD Thesis
- Image saliency combined with regional-based pose estimation
- [Project page]
- [STS-135 ISS undocking infrared camera pose estimation, video]
- [STS-135 ISS undocking LIDAR Ranging, video]
- [STS-135 ISS docking infrared camera pose estimation, video]
- [STS-135 ISS pose estimation gradient descent, video]
- [RSM thermal image pose estimation, video]
- [Gradient descent initialisation using FC-HSF, video]
- [Envisat pose estimation 3D view, video]
- [Enhanced gradient descent, video]
- [Level-set evolution, video]
- [STS-135 ISS image saliency foreground prediction, video]
- [Image saliency and regional-based pose estimation, paper]
- Image saliency
- Pose estimation using Level-set regional statistics approach
- Deep learning
- Real-time Mobile Object Detection
- ISS Free-flyer Detection
- Spacecraft Testbed Detection
- Cubesat Detection and Localisation
- Facial Emotion Recognition
- Spacecraft Image Segmentation
- Machine learning for object detection and recognition
- Image features
- Appearance-based pose estimation using Principal Components Analysis (PCA)
- Pose estimation using iterative and non-iterative Perspective-n-Point (PnP)
- Spacecraft GNC
- Spacecraft and Manipulator Simulation
- Flexible body dynamics, contact dynamics
- Orbital mechanics, spacecraft attitude dynamics, proximity operations, free-flyer capture
- Manipulator kinematics
- Mechatronics
- Gyrodampers (Single Axis Control Moment Gyro)
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