Cognitive Vision Systems
1
2012-2013
03000013
Electrical and Computer Engineering
Portuguese
English
Face-to-face
6.0
Elective
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)
NoSyllabus
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