Symbols, Patterns and Signals
Welcome to COMS21202. For general information, see the syllabus for the unit.
Below are organisational details and supporting materials for the unit.
Staff
- Andrew Calway, email andrew@cs.bris.ac.uk, office 3.27 MVB.
- Peter Flach, email flach@cs.bris.ac.uk, office 3.26 MVB,
- Majid Mirmehdi, email majid@cs.bris.ac.uk, office 3.11 MVB. Unit Director.
Lectures
Lectures are as follows:
| weeks | day | time | place | type |
|---|---|---|---|---|
| 13-24 | Fri | 14:00 (1 h) | QB 1.18 | Lecture |
| 13-24 | Fri | 15:00 (1 h) | QB 1.8 | Lecture |
| 13-24 | Fri | 16:10 (1 h) | QB 1.8 | Lecture |
During the first four weeks you need to work on self-study exercises in your lab sessions:
Problem Sheets
- Coming soon .....
Assessment
Assessment is as follows:
- Three in-class tests and two coursework assignments: 50%
- In-class tests (10%)
- Exam: 50%
Unit Outline
| Lectures | Subject | Lecturer |
| 1-9 | Data and Data Modelling | ADC |
| 10-18 | Classification, Clustering and Estimation | PF |
| 19-29 | Representation, Transformation and Feature Extraction | MM |
| 30-31 | Case Studies I | ADC |
| 32-33 | Case Studies II | PF |
| 34-35 | Case Studies III | MM |
Fishy Links
-
Vision system monitors fish populations
- Book: Fish Quality Control by Computer Vision
- Weighing fish using computer vision
- Recognising fish using computer vision
- Identifying and measuring fish using computer vision
-
Finding bones in fish fillets using computer vision
Lecture Slides
- Lecture 1: Printable pdf - Introduction - ADC
- Lecture 2: Printable pdf - Data Types and Acquisition - ADC
- Lecture 3: Printable pdf - Data Properties: mean and covariance - ADC
- Lecture 4: Printable pdf - Data Properties: centroids and correlation - ADC
- Lecture 5: Printable pdf - Data Modelling: deterministic - ADC [Matlab scripts: line fit, planar fit, polynomial fit]