Computational Imaging Methods (G6087)
Note to prospective students: this content is drawn from our database of current courses and modules. The detail does vary from year to year as our courses are constantly under review and continuously improving, but this information should give you a real flavour of what it is like to study at Sussex.
We’re currently reviewing teaching and assessment of our modules in light of the COVID-19 situation. We’ll publish the latest information as soon as possible.
Computational Imaging Methods
Module G6087
Module details for 2024/25.
15 credits
FHEQ Level 6
Module Outline
This module will develop your knowledge and understanding of recent methodological developments for image analysis and reconstruction. We will describe a variety of common use-cases and discuss limitations of current approaches and open challenges.
Key topics include:
• Principles and methods for inference in computational models of imaging data.
• Approaches for standard computer vision tasks such as segmentation, detection, and tracking.
• Generative models and their application for tasks in image synthesis and analysis.
• 3D image reconstruction for photographic and medical imaging.
A range of relevant machine learning and statistical analysis techniques will be introduced as we discuss each of these topics. You will be exposed to a range of applications across photographic and biomedical imaging domains and will learn how to develop and critique potential solutions for different problems.
This module has prerequisite requirements of prior training in fundamentals of machine learning or statistical modelling, relevant mathematics (linear algebra, probability, optimisation) and programming in a suitable language.
Module learning outcomes
Demonstrate systematic understanding of the key methodological principles in image analysis and reconstruction
Demonstrate critical awareness of limitations and challenges when applying an analysis approach to a specified problem or dataset
Propose methodological solutions, based on recent research, for a specified imaging problem
Critically evaluate an implemented system
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 100.00% | |
| Coursework components. Weighted as shown below. | ||
| Report | A1 Week 1 | 100.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Autumn Semester | Lecture | 1 hour | 11111111111 |
| Autumn Semester | Seminar | 1 hour | 11111111111 |
| Autumn Semester | Laboratory | 2 hours | 11111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Please note that the University will use all reasonable endeavours to deliver courses and modules in accordance with the descriptions set out here. However, the University keeps its courses and modules under review with the aim of enhancing quality. Some changes may therefore be made to the form or content of courses or modules shown as part of the normal process of curriculum management.
The University reserves the right to make changes to the contents or methods of delivery of, or to discontinue, merge or combine modules, if such action is reasonably considered necessary by the University. If there are not sufficient student numbers to make a module viable, the University reserves the right to cancel such a module. If the University withdraws or discontinues a module, it will use its reasonable endeavours to provide a suitable alternative module.