PhD Studentship: Domain Specific Optimisation Techniques for Real-time Image/Signal Processing on Heterogeneous FPGA+CPU platform - March 2019
The increasing pervasion of vision systems in a number of application fields like machine vision, autonomous vehicles and systems, wearable and mobile devices, object detection and tracking, brings with it the need for the development of efficient and low power data and image processing capabilities. The speed and complexity of computation required dictate hardware based solutions to ensure fastest possible execution of algorithms with the lowest power requirement. Typically these types of solutions have been investigated through CPU/GPU development systems and requiring a complex and custom process for compiling to silicon for an efficient implementation of the end system.
The availability of more advanced hardware development platforms combining FPGA, CPUs and GPUs, with various interface and such as the Xilinx Zynq Ultrascale+ MPSoC lead to an interesting and timely point in this development flow. Such systems can bring together some of the flexibility benefits of high level computation through CPUs while retaining the efficiency and speed of direct hardware implementations. What needs to be understood and researched is the most efficient way to develop and implement systems in this heterogeneous computing platform. Research will focus on the development of domain specific optimization techniques for image processing accelerators and computing methods to support the image processing and analysis requirements of developing markets allied to the industrial partner’s activities.
Jointly sponsored by STMicroelectronics Imaging Division and the University of Stirling, the project will be focussed on real industrial and product development requirements and will require the implementation of key algorithms with stringent power, memory and speed efficiency targets. These developments will, in the first instance, feed and support the technology development process for STMicroelectronics Imaging Division, but will also develop into the more complex aspects of object detection, classification, tracking and segmentation - to feed into product development capabilities.
- PhD Studentship [self-funded]: Modelling and classifying concealed face recognition - Jan 2021
- PhD Studentship: Animal health in marine ecosystems: machine learning and data science to discover structure in unstructured data - March 2019
- [2019-2022] (ST Microelectronics/Univresity of Stirling: £143.75K) PhD studentship: Domain specific optimisations for real-time image processing on heterogeneous FPGA+CPU+GPU
- [2019-2023] (Scotland's Rural College/Univresity of Stirling: £79K) PhD studentship: Improving animal health in marine ecosystem using data mining and signal/image processing