BMM0046 Computer Vision

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code BMM0046
Name Computer Vision
Term 2022-2023 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator


Course Goal / Objective

Transferring the basics of Computer Vision, reaching the level where students can develop software for some hardware.

Course Content

Geometric Transformations, Perception and Tracking of Different Organs I: Face, Eye, Detection and Tracking of Different Organs II: Ear, Mouth, Feature Extraction from Image, Detection of Shapes and Image Segmentation, Object Tracking, Object Recognition, Augmented Reality, Basic Artificial Intelligence Algorithms for Computer Vision,

Course Precondition

None

Resources

G. Garrido, P. Joshi, "OpenCV 3.x with Python By Example 2E"

Notes

K Dawson-Howe, "A Practical Introduction to Computer Vision with OpenCV"


Course Learning Outcomes

Order Course Learning Outcomes
LO01 The student can develop software that can perform real-time object tracking.
LO02 Develop software that will parse different objects in real time.
LO03 Can develop computer vision projects for basic hardware other than computers.
LO04 Can apply artificial intelligence methods for computer vision.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal To be able to reach new solutions by applying current and advanced technical approaches of mathematics, science and engineering sciences to current scientific problems encountered in the field of medicine and medical technologies. 5
PLO02 Yetkinlikler - Öğrenme Yetkinliği Having knowledge of the literature related to a sub-discipline of biomedical engineering, defining and modeling current problems, and being a specialist in that discipline. 5
PLO03 Beceriler - Bilişsel, Uygulamalı Analyzing data, making theoretical and simulation based designs, designing experiments and interpreting the results. 5
PLO04 Beceriler - Bilişsel, Uygulamalı Developing researched contemporary techniques, software, hardware and computational tools for engineering applications. 5
PLO05 Beceriler - Bilişsel, Uygulamalı To be able to analyze and design a process in line with a defined target.
PLO06 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği To be able to carry out scientific studies with medical doctors and members of other disciplines from an engineering point of view.
PLO07 Yetkinlikler - İletişim ve Sosyal Yetkinlik Expressing one's own findings orally and in writing, clearly and concisely, writing conference and journal papers.
PLO08 Yetkinlikler - Öğrenme Yetkinliği To be able to improve oneself by embracing the importance of lifelong learning and by following the developments in science-technology and contemporary issues.
PLO09 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği The ability to act independently, set priorities and be creative.
PLO10 Yetkinlikler - Alana Özgü Yetkinlik Being aware of national and international contemporary scientific and social problems in the field of Biomedical Engineering.
PLO11 Yetkinlikler - Alana Özgü Yetkinlik To be able to evaluate the contribution of engineering solutions to problems in medicine, medical technologies and health in a global and social context.


Week Plan

Week Topic Preparation Methods
1 Introduction of Software Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
2 Geometric Transformations Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
3 Perception and Tracking of Different Organs I: Face, Eye Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
4 Detection and Tracking of Different Organs II: Ear, Mouth Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
5 Feature Extraction from Image I Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
6 Feature Extraction from Image II Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
7 Detection of Shapes and Image Segmentation Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Review Ölçme Yöntemleri:
Yazılı Sınav
9 Object Tracking I Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
10 Object Tracking II Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
11 Object Recognition I Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
12 Object Recognition II Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
13 Augmented Reality Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
14 Basic Artificial Intelligence Algorithms for Computer Vision I Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
15 Basic Artificial Intelligence Algorithms for Computer Vision II Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
16 Term Exams Review Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Review Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 16.11.2022 06:44