Qualification Type: | PhD |
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Location: | Swansea |
Funding for: | UK Students |
Funding amount: | £17,668 p.a. annual stipend |
Hours: | Full Time |
Placed On: | 2nd December 2022 |
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Closes: | 18th January 2023 |
Funding providers: Engineering and Physical Sciences Research Council (EPSRC) DTP and Swansea University's Faculty of Science and Engineering
Subject areas: Artificial Intelligence, Image Analysis
Project start date:
Project description:
The availability of free satellite images in medium/high spatial resolution has enabled possible solutions for the challenging dynamic land use and land cover mapping problems. This project is about developing new AI techniques for crop detection and mapping.
Crop detection is the first step in AI-based time series analyses, aiming to provide fundamental information for many socio-economic applications. Examples are crop control and yield estimation, change monitoring, supply chain and food security, climate change policies such as crop rotation, insurance, and fertilization services.
The lack of ground truth data is a major problem for crop detection. That is the case for most time-series analyses of historical data. On the other hand, the crop-specific variations in visual and chemical characteristics during a year are sensed by spectral satellite images. Therefore, this project is focused on developing AI techniques effectively utilizing the spectral bands for crop detection. This is achieved based on (1) an unsupervised framework to identify effective spectral bands for time-series analysis and crop detection. For this aim, the crops fingerprints and other vegetation indexes are used to identify the important spectral wavelengths. (2) a supervised framework for developing a novel spectral attention model using visual transformers prediction strategies.
Eligibility
Candidates must normally hold an undergraduate degree at 2.1 level plus a recognised master's degree with Merit (or Non-UK equivalent as defined by Swansea University) in Data Science, Computer Science, Mathematics, Industrial Engineering or closely related discipline.
English Language requirements: If applicable – IELTS 6.5 overall (with at least 5.5 in each individual component) or Swansea recognised equivalent.
Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.
Funding
This scholarship covers the full cost of UK tuition fees and an annual stipend of £17,668.
Additional research expenses will also be available.
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