DD2427 Image Based Recognition and Classification 6.0 credits
Bildbaserad igenkänning och klassificering
A course in computer science focusing on basic theory, models, and methods for classification of data with special emphasis on object recognition in digital images.
| Academic level (A-D) | D | Subject area | |
| Educational level | 2 | Grade scale | A, B, C, D, E, FX, F |
Spring 10 bik10 for programme students
| Periods | 4 (6.0 cr) | Application code | 80369 |
| Start date | End date | ||
| Language of instruction | English | Campus | KTH Campus |
| Course pace | 100% | Tutoring time | Daytime |
| Number of places | Form of study | NML | |
| Course responsible | |||
| Teacher | |||
| Target group | All who have the required prior knowledge |
||
Goals
After the course you should be able to:
- identify basic notions, terminology, theories models and methods for classification of data,
- develop and systematically evaluate a number of basic methods for classification of data,
- experimentally evaluate algorithms for classification and recognition of objects in digital gray value images,
- choose appropriate method in order to automatically solve a given classification problem,
- know about theories of how the brain processes visual information for classification,
in order to
- be able to solve general problems of data representation and classification,
- be able to implement, analyze and evaluate simple systems for automatic classification of images,
- obtain a broad base of knowledge in order to be able to acquire information about and read literature in the field.
Content
- Representation and feature extraction in digital images
- principles of recognition and classification, Bayesian decisions
- discriminant functions, neural networks, support vector machines
- learning, optimization of classifiers
- overview of recognition in biological systems
- examples of recognition: handwritten text, faces, objects.
Eligibility
Prerequisites
Knowledge corresponding to the compulsory courses on mathematics, computer science and numerical analysis on D-, E- or F-programme.
Literature
Material produced at the department.
Examination
- INL1 - Assignment, 1.5 credits, grade scale: P, F
- LAB1 - Laboratory Work, 1.5 credits, grade scale: P, F
- TEN1 - Examination, 3.0 credits, grade scale: A, B, C, D, E, FX, F
In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.
Requirements for final grade
Laboratory assignments (LAB1; 1,5 university credits)
Hand in exercise (INL1; 1,5 university credits)
Examination (TEN1; 3 university credits )
Offered by
CSC/Computer Science
Contact
Josephine Sullivan, tel: 790 6136, e-post: sullivan@nada.kth.se
Examiner
Ordinarie examinator är Stefan Carlsson.
Add-on studies
Discuss with course leader.
Version
Course plan valid from: Autumn 09.
