COMP 482 Computer VisionMEF ÜniversitesiAkademik Programlar Bilgisayar MühendisliğiÖğrenciler için Genel BilgiDiploma EkiErasmus Beyanı
Bilgisayar Mühendisliği
Lisans Programın Süresi: 4 Kredi Sayısı: 240 TYYÇ: 6. Düzey QF-EHEA: 1. Düzey EQF: 6. Düzey

Ders Genel Tanıtım Bilgileri

School/Faculty/Institute Faculty of Engineering
Course Code COMP 482
Course Title in English Computer Vision
Course Title in Turkish Bilgisayarla Görü
Language of Instruction EN
Type of Course Flipped Classroom
Level of Course Introductory
Semester Güz
Contact Hours per Week
Lecture: 3 Recitation: None Lab: None Other: None
Estimated Student Workload 161 hours per semester
Number of Credits 6 ECTS
Grading Mode Standard Letter Grade
Pre-requisites COMP 106 - Object-Oriented Programming | COMP 110 - Object-Oriented Programming (JAVA)
Expected Prior Knowledge Object Oriented Programming, Data Structures
Co-requisites None
Registration Restrictions Only Undergraduate Students
Overall Educational Objective To become familiar with the fundamental concepts of Computer Vision, such as image formation, camera parameters, preprocessing, convolution, segmentation, edge and corner detection, line and ellipse fitting, image understanding and object recognition.
Course Description This course provides a comprehensive introduction to some fundamental aspects of Computer Vision. The following topics are covered: Introduction, Image formation, camera parameters, preprocessing, convolution, segmentation, edge and corner detection, line and ellipse fitting, Object Tracking, image understanding and object recognition, Deep Learning.
Course Description in Turkish Bu derste; bilgisayarla görünün temel kavramları şu konu başlıklar altında kapsamlı bir şekilde incelenmektedir: Giriş, görüntü oluşumu, kamera parametreleri, önişleme, evriştirme, bölütleme, kenar ve köşe bulma, doğru ve elips uydurma, görüntü analizi, nesne tanıma ve derin öğrenme.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
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Program Learning Outcomes/Course Learning Outcomes 1 2 3 4 5 6 7 8 9
1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
3) An ability to communicate effectively with a range of audiences
4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts
5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

Relation to Program Outcomes and Competences

N None S Supportive H Highly Related
     
Program Outcomes and Competences Level Assessed by
1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics H Exam,HW,Project
2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors H Exam,HW,Project
3) An ability to communicate effectively with a range of audiences S Project
4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts N
5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives N
6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions S Exam,HW,Project
7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. S Exam,HW,Project
Prepared by and Date MUHİTTİN GÖKMEN , April 2018
Course Coordinator MUHİTTİN GÖKMEN
Semester Güz
Name of Instructor Prof. Dr. MUHİTTİN GÖKMEN

Course Contents

Hafta Konu
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Required/Recommended ReadingsComputer Vision: Algorithms and Applications, Richard Szeliski, Springer Science & Business Media, 2010 Introductory Techniques for 3-D Computer Vision, by Emanuele Trucco, Alessandro Verri, Prentice-Hall, 1998
Teaching MethodsLecturing and exercises in the classroom with computers. In-class exercises and 3 Projects will be carried out by students
Homework and ProjectsIn-class exercises, 2 Projects, 2 Midterm exams, Term project
Laboratory WorkProgramming exercises
Computer UseFor Programming
Other ActivitiesNone
Assessment Methods
Assessment Tools Count Weight
Küçük Sınavlar 3 % 10
Projeler 3 % 50
Ara Sınavlar 1 % 40
TOTAL % 100
Course Administration gokmenm@mef.edu.tr

Instructor’s office and phone number, office hours, email address: To be announced -Office: 5th Floor, #18 -Phone number: 0 212 395 36 26 - Email address: gokmenm@mef.edu.tr Rules for attendance: Minimum of 70% attendance required. Missing a quiz: Provided that proper documents of excuse are presented, each missed quiz by the student will be given a grade which is equal to the average of all of the other quizzes. No make-up will be given. Missing a midterm: Provided that proper documents of excuse are presented, each missed midterm by the student will be given the grade of the final exam. No make-up will be given. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations http://3fcampus.mef.edu.tr/uploads/cms/webadmin.mef.edu.tr/4833_2.pdf

ECTS Student Workload Estimation

Activity No/Weeks Hours Calculation
No/Weeks per Semester Preparing for the Activity Spent in the Activity Itself Completing the Activity Requirements
Ders Saati 14 1 3 1 70
Proje 1 35 7 42
Küçük Sınavlar 3 4 1 15
Ara Sınavlar 2 15 2 34
Total Workload 161
Total Workload/25 6.4
ECTS 6