Additional
information for the course
|
Mini module |
Content |
Time &
Place |
|
Introduction,
spatial redundancy, and compression |
12.30 15/3- |
|
|
Transformation
of data |
12.30 22/3- |
|
|
Dimensionality
reduction |
12.30 19/4- |
|
|
Orthogonal regression, Incomplete datasets,
Expectation-Maximization (EM) |
12.30 12/4- |
|
|
Student
presentations of mini projects |
14.30 19/4- |
Each
link will be updated with detailed info no later than 2 days prior to
the
lecture.
The literature for the course will be provided
as downloads. See individual mini modules.
Thomas
Moeslund,
Hans Jørgen Andersen,
NOVI III, 3-111
Instead of
individual exercises following each mini module one mini project will
be
carried out. The content of the mini project will be presented in the
first
mini module. During the last mini module each student group will give
an
informal presentation of their mini project followed by a brief
discussion in
the class.
The mini
project will form the basis for the "evaluation". Discussions during
exercise time and the informal presentation of the mini project in the
last
mini module will constitute the basis for a "pass or no pass"
judgement. This is only relevant to those taking the course as "free
study
activity".