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| Offered by:
Department of Applied Electronics
(IAE) |
| Prerequisite: 92062 |
| Recommended semester:
5th or 6th semester |
| Scope and form: Class lectures and project work. |
| Examination:
Evaluation of report and oral presentation
(13 point scale
) |
Remarks: A project has to be performed during the semester and documented in a report.
The project is solved in groups of two students.
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| Contact person: |
Jørn Bang, IAE, Building 451, Tel. +45 4525 5236 |
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Aim: The objective of the course is to enable the student to:
- design and apply recognition algorithms for automatic recognition of objects in computer images e.g. recognition of errors in industrial products based on images of these,
- analyse, process and recognize patterns from time signals and digital computer images,
- understand classical and modern 1- and 2-dimensional pattern recognition methods, and
- apply pattern recognition methods using modern lab. tools. |
Contents: Introduction to pattern analysis, -processing, and -recognition.
Bayes decision methods. Parameter estimation and supervised learning.
Non-parametric methods. Linear discriminant functions. Unsupervised learning and clustering. Dynamic time warping.
Introduction to Markov-based pattern recognition. Pattern recognition methods.
Automatic speech recognition for machine control.
Automatic recognition of objects in images from industrial production systems.
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