COURSE UNIT TITLE

: COMPUTER VISION

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EEE 5034 COMPUTER VISION ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR HATICE DOĞAN

Offered to

ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING NON -THESIS (EVENING PROGRAM) (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)

Course Objective

The aim of the course is to provide the students with theoretical knowledge about the processing and interpretation of visual information and to enable them to apply this in computer vision processes. Students create designs and solve real-world problems using what they have learned in the course.

Learning Outcomes of the Course Unit

1   To be able to design solutions to real-world problems using computer vision.
2   To be able develop working computer vision systems using MATLAB.
3   To be able to critically appraise computer vision techniques.
4   To be able to explain, compare and contrast computer vision techniques.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Computer Vision
2 Image formation
3 Image Filtering
4 Image Features -I
5 Image Features -II
6 Image Segmentation
7 Shape Descriptors
8 Image Classification
9 Object Recognition-I
10 Object Recognition-II
11 Neural Networks-I
12 Neural Networks-II
13 Computer Vision Applications-I
14 Computer Vision Applications-II

Recomended or Required Reading

Computer Vision Algorithms and Applications, Richard Szeliski, Springer, 2010
Computer Vision: A Modern Approach, Forsyth and Ponce, Pearson, 2003

Planned Learning Activities and Teaching Methods

Lecture+Assignments +Exam

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 MTE MIDTERM EXAM
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE ASG * 0.30 + MTE * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.30 + MTE * 0.30 + RST * 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

hatice.dogan@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 3 42
Preparing assignments 5 15 75
Preparation for midterm exam 1 15 15
Preparation for final exam 1 20 20
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 198

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.1544353443
LO.2343343443
LO.33412321
LO.4323132111

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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