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About the Project
These projects are open to students worldwide, but have no funding attached. Therefore, the successful applicant will be expected to fund tuition fees at the relevant level (home or international) and any applicable additional research costs. Please consider this before applying.
This project aims to develop a lightweight instance segmentation model to deploy in edge device like Jetson Nano Orin. For example, sustainable development can be used lightweight instance segmentation to accelerate the sustainable fishing and avoid unwanted catch. When insufficient data is available one-few or few-shot learning will be used to tackle the problem.
Essential Background:
Decisions will be based on academic merit. The successful applicant should have, or expect to obtain, a UK Honours Degree at 2.1 (or equivalent) in Computer Science, Robotics, Electrical, Electronic, Mechanical engineering or related fields.
Desirable knowledge:
A relevant Master’s degree and/or experience in one of the above will be an advantage.
Application Procedure:
Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php.
You should apply for Computing Science (PhD) to ensure your application is passed to the correct team for processing.
Please clearly note the name of the lead supervisor and project title on the application form. If you do not include these details, it may not be considered for the studentship.
Your application must include: A personal statement, an up-to-date copy of your academic CV, and clear copies of your educational certificates and transcripts.
Please note: you DO NOT need to provide a research proposal with this application.
If you require any additional assistance in submitting your application or have any queries about the application process, please don't hesitate to contact us at pgrs-admissions@abdn.ac.uk
Funding Notes
This is a self-funding project open to students worldwide. Our typical start dates for this programme are February or October.
Fees for this programme can be found here Finance and Funding | Study Here | The University of Aberdeen (abdn.ac.uk)
Additional research costs / bench fees may also apply and will be discussed prior to any offer being made.
References
[1] Yang, Yong, Qiong Chen, Yuan Feng, and Tianlin Huang. "MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentation." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7131-7140. 2023.
[2] Han, Yue, Jiangning Zhang, Zhucun Xue, Chao Xu, Xintian Shen, Yabiao Wang, Chengjie Wang, Yong Liu, and Xiangtai Li. "Reference twice: A simple and unified baseline for few-shot instance segmentation." arXiv preprint arXiv:2301.01156 (2023).
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