BİLGİSAYAR MÜHENDİSLİĞİ (YL) (TEZLİ) (İNGİLİZCE) | |||||
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Qualification Awarded | Program Süresi | Toplam Kredi (AKTS) | Öğretim Şekli | Yeterliliğin Düzeyi ve Öğrenme Alanı | |
2 | 120 | FULL TIME |
TYÇ, TR-NQF-HE, EQF-LLL, ISCED (2011):Level 7 QF-EHEA:Second Cycle TR-NQF-HE, ISCED (1997-2013): 48,52 |
Course Code: | 3017002045 | ||||||||||
Ders İsmi: | Computer Vision | ||||||||||
Ders Yarıyılı: | Spring | ||||||||||
Ders Kredileri: |
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Language of instruction: | EN | ||||||||||
Ders Koşulu: | |||||||||||
Ders İş Deneyimini Gerektiriyor mu?: | No | ||||||||||
Other Recommended Topics for the Course: | |||||||||||
Type of course: | Department Elective | ||||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||||
Course Coordinator : | Dr.Öğr.Üyesi Recep DURANAY | ||||||||||
Course Lecturer(s): | |||||||||||
Course Assistants: |
Course Objectives: | This course is for students who want to learn about the basic principles and applications of computer vision. Basic concepts of computer vision will be introduced in the course. The practical applications of computer vision, which are important in our daily life, will be discussed. Students will participate in the project where they can apply computer vision algorithms. |
Course Content: | This course will cover image rendering, signal processing, feature detection matching, segmentation, feature-based alignment, motion-to-structure, dense motion estimation, image stitching, computational photography, stereo-matching, three-dimensional reconstruction, image-based rendering and recognition. |
The students who have succeeded in this course;
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Week | Subject | Related Preparation |
1) | Görüntü oluşumu / projektif geometri / aydınlatma | |
2) | pratik lineer cebir | |
3) | Görüntü işleme / tanımlayıcılar | |
4) | görüntü eğilmesi | |
5) | Doğrusal modeller + optimizasyon | |
6) | Sinir ağları | |
7) | Sinir ağları | |
8) | Midterm | |
9) | Sinir ağlarının uygulamaları | |
10) | Hareket ve akış | |
11) | Single-view geometry | |
12) | Multi-view geometry | |
13) | Applications | |
14) | Applications | |
15) | Final |
Course Notes / Textbooks: | Szeliski, Richard. Computer vision: algorithms and applications. Springer Science & Business Media, 2010. |
References: | Szeliski, Richard. Computer vision: algorithms and applications. Springer Science & Business Media, 2010. |
Ders Öğrenme Kazanımları | 1 |
2 |
3 |
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Program Outcomes | |||||||||
1) Ability to reach wide and deep knowledge through scientific research in the field of Computer Science and Engineering, evaluate, interpret and apply. | |||||||||
2) Ability to use scientific methods to cover and apply limited or missing knowledge, and to integrate the knowledge of different disciplines. | |||||||||
3) Ability to construct Computer Science and Engineering problems, develop methods to solve the problems and use innovative methods in the solution. | |||||||||
4) Ability to develop new and/or original ideas and algorithm; develop innovative solutions in the design of system, component or process. | |||||||||
5) Ability to have extensive knowledge about current techniques and methods applied in Computer Engineering and their constraints. | |||||||||
6) Ability to design and implement analytical modeling and experimental research, solve and interpret complex situations encountered in the process. | |||||||||
7) Ability to use a foreign language (English) at least at the level of European Language Portfolio B2 in verbal and written communication. | |||||||||
8) Ability to lead in multidisciplinary teams, develop solutions to complex situations and take responsibility. | |||||||||
9) Awareness of the social, legal, ethical and moral values, and the ability to conduct research and implementation work within the framework of these values. | |||||||||
10) Awareness of the new and emerging applications in Computer Science and Engineering field, and the ability to examine them and learn if necessary. |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Ability to reach wide and deep knowledge through scientific research in the field of Computer Science and Engineering, evaluate, interpret and apply. | |
2) | Ability to use scientific methods to cover and apply limited or missing knowledge, and to integrate the knowledge of different disciplines. | |
3) | Ability to construct Computer Science and Engineering problems, develop methods to solve the problems and use innovative methods in the solution. | |
4) | Ability to develop new and/or original ideas and algorithm; develop innovative solutions in the design of system, component or process. | |
5) | Ability to have extensive knowledge about current techniques and methods applied in Computer Engineering and their constraints. | |
6) | Ability to design and implement analytical modeling and experimental research, solve and interpret complex situations encountered in the process. | |
7) | Ability to use a foreign language (English) at least at the level of European Language Portfolio B2 in verbal and written communication. | |
8) | Ability to lead in multidisciplinary teams, develop solutions to complex situations and take responsibility. | |
9) | Awareness of the social, legal, ethical and moral values, and the ability to conduct research and implementation work within the framework of these values. | |
10) | Awareness of the new and emerging applications in Computer Science and Engineering field, and the ability to examine them and learn if necessary. |
Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama) | |
Homework | |
Bireysel Proje | |
Raporlama |
Semester Requirements | Number of Activities | Level of Contribution |
Homework Assignments | 2 | % 10 |
Project | 1 | % 15 |
Midterms | 1 | % 20 |
Paper Submission | 1 | % 15 |
Semester Final Exam | 1 | % 40 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 60 | |
PERCENTAGE OF FINAL WORK | % 40 | |
total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Homework Assignments | 3 | 30 | 90 |
Midterms | 1 | 2 | 2 |
Paper Submission | 14 | 3 | 42 |
Final | 1 | 3 | 3 |
Total Workload | 179 |