Last modified: 31 Jul 2023 11:19
Nowadays a large volume of data is stored in form of images. This course introduces the tools needed to analyse images and extract information from them, including aspects of image enhancement, filtering, segmentation, morphological analysis and image classification based on convolutional neural networks.
| Study Type | Postgraduate | Level | 5 |
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| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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The main focus of the course is to introduce key concepts of image analysis. Emphasis will be put on the concepts underlying the algorithms to analyse images, including image enhancement, filtering (spatial and frequency domain), segmentation, morphological transformations, colour image analysis and convolutional neural networks for automatic classification of images. During the lectures, the main concepts and ideas will be explained, and during the practical sessions, we will discuss how to implement the algorithms to apply them to images. This course will therefore provide students with the fundamentals of how to process and extract information from images.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 34 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Weighting: 1/3 (33.33...%) |
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| Knowledge Level | Thinking Skill | Outcome |
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| Assessment Type | Summative | Weighting | 33 | |
|---|---|---|---|---|
| Assessment Weeks | 31 | Feedback Weeks | 33 | |
| Feedback |
Weighting: 1/3 (33.33...%) |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Assessment Type | Summative | Weighting | 33 | |
|---|---|---|---|---|
| Assessment Weeks | 31,32,33 | Feedback Weeks | 31,32,33 | |
| Feedback |
Weighting: 1/3 (33.33...%) |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Develop an understanding of the fundamental mathematical principles underlying audio and image analysis. |
| Procedural | Apply | Be able to carry out standard segmentation, filtering, recognition and other basic procedures of audio and video data analysis. |
| Procedural | Understand | Identify basic concepts, terminology and methods in the field of digital audio and image analysis. |
| Procedural | Evaluate | Develop the abilities needed to critically compare different tools and approaches of audio and image analysis and chose the ones better suited for a given task. |
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