Postgraduate Programme and Module Handbook 2023-2024 (archived)
Module PHYS52115: Data Acquisition and Image Processing
Department: Physics
PHYS52115: Data Acquisition and Image Processing
| Type | Tied | Level | 5 | Credits | 15 | Availability | Available in 2023/24 | Module Cap | None. |
|---|
| Tied to | G5K609 |
|---|
Prerequisites
- None
Corequisites
- PHYS51915 Core Ia: Introduction to Machine Learning and Statistics and PHYS52015 Core Ib: Introduction to Scientific and High-performance Computing
Excluded Combination of Modules
- None
Aims
- Provide basic knowledge and critical understanding of data acquisition and image analysis
- Provide basic knowledge and critical understanding of paradigms, fundamental ideas and methods of data acquisition and image processing.
Content
- Data acquisition
- Image Processing
Learning Outcomes
Subject-specific Knowledge:
- understanding and critical reflection of fundamental ideas and techniques in the application of data acquisition.
- understanding and critical reflection of fundamental ideas and techniques in the application of image processing.
Subject-specific Skills:
- Competent and educated selection and application of data acquisition techniques and image processing for specific problems.
Key Skills:
- Familiarity with basic paradigms and modern concepts underlying data acquisition and image processing.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Teaching will be by lectures, workshops and practical classes.
- The lectures provide the means to give a concise, focused presentation of the subject matter of the module.
- When appropriate, the lectures will also be supported by the distribution of written material, or by information and relevant links on DUO
- Regular problem exercises and workshops will give students the chance to develop their theoretical understanding and problem solving skills.
- Students will be able to obtain further help in their studies by approaching their lecturers, either after lectures or at other mutually convenient times.
- Student performance will be summatively assessed through coursework.
- The formative coursework provides opportunities for feedback, for students to gauge their progress and for staff to monitor progress throughout the duration of the module.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | |
|---|---|---|---|---|---|
| Data Acquistion | 8 | 8 per week | 1 hour | 8 | |
| Practical Classes in Data Acquisition | 8 | 8 per week | 1 hour | 8 | |
| Image Processing | 8 | 8 per week | 1 hour | 8 | |
| Practical Classes in Image Processing | 8 | 8 per week | 1 hour | 8 | |
| Self-study | 118 | ||||
| Total | 150 |
Summative Assessment
| Component: Coursework | Component Weighting: 100% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Data Acquisition Coursework | 50% | ||
| Image Processing Coursework | 50% | ||
Formative Assessment:
Feedback on coursework
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University