Module Details |
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
Title | Computer Vision | ||
Code | COMP338 | ||
Coordinator |
Dr AQ Nguyen Computer Science Anh.Nguyen@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2022-23 | Level 6 FHEQ | First Semester | 15 |
Aims |
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To provide an introduction to the topic of Computer Vision. |
Learning Outcomes |
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(LO1) Demonstrate an understanding of the theoretical and practical aspects of image representations. |
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(LO2) Describe state-of-the-art techniques for image classification, image search, image segmentation, object detection, and object tracking. |
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(LO3) Describe the foundation of image formation with the pinhole camera model and how they project the 3D world to 2D images. |
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(LO4) Apply the principles of deep neural networks to various vision problems such as classification, detection, and semantic segmentation. |
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(LO5) Demonstrate and apply the practical skills necessary to build computer vision applications. |
Syllabus |
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2D vision: 3D vision Computer Vision in the era of deep learning |
Teaching and Learning Strategies |
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Teaching Method 1 - Lecture Teaching Method 2 - Laboratory Work Due to Covid-19, in 2021/22, one or more of the following delivery methods will be implemented based on the current local conditions. (b) Fully online delivery and assessment (c) Standard on-campus delivery |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
30 |
10 |
40 | ||||
Timetable (if known) | |||||||
Private Study | 110 | ||||||
TOTAL HOURS | 150 |
Assessment |
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EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
(338) Final exam | 2.5 | 70 | ||||
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
(338.1) Programming Assignment on Image Alignment | 0 | 15 | ||||
(338.2) Programming Assignment on Deep Neural Networks | 0 | 15 |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |