Course Unit / Cognitive Vision Systems

Cognitive Vision Systems

Year
1
Academic year
2012-2013
Code
03000013
Subject Area
Electrical and Computer Engineering
Language of Instruction
Portuguese
Other Languages of Instruction
English
Mode of Delivery
Face-to-face
ECTS Credits
6.0
Type
Elective
Level
3rd Cycle Studies

Recommended Prerequisites

Algebra, Analysis, Signals and Systems, Control, Computational Mathematics.

Teaching Methods

Teaching includes theoretical classes using slides and after the basis having been introduced seminars prepared by the students on topics previously agreed upon.

Learning Outcomes

The goals of this unit include teaching the foundations and concepts associated to Bayesian models used in problems of image analysis, image segmentation and image classification.

Work Placement(s)

No

Syllabus

Probability. Probability models. Modeling complex data densities. Regression models. Classification models. Graphical models.

Head Lecturer(s)

Hélder de Jesus Araújo

Assessment Methods

Assessment
Evaluation is either performed based on Matlab computational projects (100%) or Matlab computational projects (50%) and a final test (50%): 100.0%

Bibliography

“Computer vision: models, learning and inference”, Simon Prince

“Bayesian Reasoning and Machine Learning”, David Barber