COURSE UNIT TITLE

: COMPUTER GRAPHICS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CME 4409 COMPUTER GRAPHICS ELECTIVE 2 2 0 6

Offered By

Computer Engineering (English)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR DERYA BIRANT

Offered to

Computer Engineering (English)

Course Objective

This course aims to provide a comprehensive introduction to computer vision through deep learning techniques.

Learning Outcomes of the Course Unit

1   Explain basic concepts, components and methods.
2   Apply algorithms based on the subject
3   Develop models
4   Design project and implement software
5   Provide computer visual recognition

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 Classification
3 Loss Functions and Optimization
4 Introduction to Neural Networks
5 Convolutional Neural Networks
6 Training Neural Networks
7 Deep Learning Software
8 CNN Architectures
9 Recurrent Neural Networks
10 Detection and Segmentation
11 Visualizing and Understanding
12 Generative Models
13 Deep Reinforcement Learning
14 Efficient Methods and Hardware for Deep Learning

Recomended or Required Reading

Textbook:Computer Graphics Using OpenGL, 3. Ed. , Francis S. Hill, Prentice Hall, 2006, ISBN 10: 013149670
Complementary Books:The OpenGL Programming Guide: The Official Guide to Learning OpenGL, 4th Ed., Dave Shreiner, M. Woo, J. Neider, Addison Wesley,
2006, ISBN 10: 0201604582
References:
Other course materials: Mathematics for 3D Game Programming and Computer Graphics, 2. Ed., Eric Lengyel, Charles River Media, 2003, ISBN 10: 15845027790.
- Redbook, Bluebook.

Planned Learning Activities and Teaching Methods

Lectures
Presentation
Laboratory exercises
Project

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.20 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.20 + RST * 0.50


Further Notes About Assessment Methods


Assessment Criteria

Midterm, Assignment, Project

Language of Instruction

English

Course Policies and Rules

1. Participation is mandatory (%70 theoretical courses and 80% practices).
2. Instructor reserves the right to quizzes. Notes should be added to these examinations, midterm and final exam grades.

Contact Details for the Lecturer(s)

Assoc.Prof.Dr. Semih UTKU
Dokuz Eylül Üniversitesi
Bilgisayar Mühendisliği Bölümü
Tınaztepe Yerleşkesi 35160 BUCA/IZMIR
Tel: (232) 301 74 28
E-Posta: semih@cs.deu.edu.tr

Office Hours

Tuesday 10:00 - 12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Tutorials 14 2 28
Preparation for midterm exam 1 6 6
Preparation for final exam 1 8 8
Preparing assignments 4 10 40
Lab Preparation 14 2 28
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 144

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1322
LO.2523
LO.35
LO.454343
LO.5354

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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