Dr. Dirk Schnieders
Mr. Huiquan Zhou
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.
| Course Learning Outcomes | Relevant Programme Learning Outcome |
| CLO1. An understanding of the fundamental concepts and the mathematical tools used in digital image processing and computer vision | PLO.5, 6, 7, 8, 9, 16 |
| CLO2. Able to design and implement various algorithms for digital image processing and computer vision | PLO.6, 7, 8, 9, 10, 11, 12 |
| View Programme Learning Outcomes | |
| Course Content | No. of Hours | Course Learning Outcomes |
| 1. Introduction | 3 | CLO1 |
| 2. Digital Image Fundamentals | 2 | CLO1 |
| 3. Image Enhancement | 6 | CLO1, CLO2 |
| 4. Image Restoration | 2 | CLO1, CLO2 |
| 5. KNN and Artificial Neural Networks | 6 | CLO1, CLO2 |
| 6. Deep Learning with Convolutional Neural Networks | 5 | CLO1, CLO2 |
| 7. Group Presentations | 6 | CLO2 |
| Description | Type | Weighting * | Examination Period ^ | Course Learning Outcomes |
| Programming Assignment | Continuous Assessment | 30% | - | CLO2 |
| Written Midterm Examination | Continuous Assessment | 20% | - | CLO1 |
| Written exam covering all taught content of the course | Written Examination | 50% | August 13 to 18, 2018 | CLO1 |
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* The weighting of coursework and
examination marks is subject to approval
^ The exact examination date uses to be released when all enrolments are confirmed after add/drop period by the Examinations Office. Students must oblige to the examination schedule. Students should NOT enrol in the course if they are not certain that they will be in Hong Kong during the examination period. Absent from examination may result in failure in the course. There is no supplementary examination for all MSc curriculums in the Faculty of Engineering. For reference:
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- Available from the course web page
| Date | Time | Venue | Remark | |
| Session 1 | 11 Jun 2018 (Mon) | 7:00pm - 10:00pm | CB-C | |
| Session 2 | 13 Jun 2018 (Wed) | 7:00pm - 10:00pm | CB-C | |
| Session 3 | 16 Jun 2018 (Sat) | 9:30am - 12:30pm | CB-C | |
| Session 4 | 30 Jun 2018 (Sat) | 9:30am - 12:30pm | CB-C | |
| Session 5 | 4 Jul 2018 (Wed) | 7:00pm - 10:00pm | CB-C | |
| Session 6 | 7 Jul 2018 (Sat) | 9:30am - 12:30pm | CB-C | |
| Session 7 | 11 Jul 2018 (Wed) | 7:00pm - 10:00pm | CB-C | |
| Session 8 | 14 Jul 2018 (Sat) | 9:30am - 12:30pm | CB-C | |
| Session 9 | 4 Aug 2018 (Sat) | 9:30am - 12:30pm | CB-C | |
| Session 10 | 4 Aug 2018 (Sat) | 1:30pm - 4:30pm | CB-C | |
| CB - Chow Yei Ching Building | ||||
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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.