Instructor |
Dr. Dirk Schnieders
|
Teaching assistant |
Mr. Huiquan Zhou
|
Syllabus |
To study the theory and algorithms in image processing and computer vision.
Topics include image representation; image enhancement; image restoration;
mathematical morphology; image compression; scene understanding and motion
analysis. |
Introduction by Instructor |
This course will study both theory and applications of image processing and
computer vision.
The first part of this course will cover digital
image processing for the improvement of pictorial information for human and
machine interpretation. Students will enhance and restore images in the
spatial domain using convolution. The second part of this course will focus
on computer vision, including feature extraction and deep learning with
convolution neural networks for image classification. |
Learning Outcomes |
|
Pre-requisites |
Good programming, knowledge of probability and linear algebra. |
Compatibility |
|
Topics covered |
|
Assessment |
|
Course materials |
Lecture Notes & Lab Instructions:
- Available from the course web page
|
Session dates |
|
Add/drop |
11 June, 2018 - 13 June, 2018 |
Quota |
100 |
Moodle course website |
-
HKU Moodle:
http://moodle.hku.hk/course/view.php?id=57210
(Login using your HKU Portal UID and PIN)
- Please note that the instructor maintains and controls when to release the Moodle teaching website to students.
- Enrolled students should visit the Moodle teaching website regularly for latest announcements, course materials, assignment submission, discussion forum, etc.
|