Course Detail
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|
| EMBEDDED ARTIFICIAL INTELLIGENCE and COMPUTER VISION | COE4215378 | Spring Semester | 2+2 | 3 | 6 |
| Course Program | Perşembe 17:30-18:15 Perşembe 18:30-19:15 Perşembe 19:30-20:15 Perşembe 20:30-21:15 |
| Prerequisites Courses | |
| Recommended Elective Courses | |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Elective |
| Course Coordinator | Prof.Dr. Bahadır Kürşat GÜNTÜRK |
| Name of Lecturer(s) | Prof.Dr. Bahadır Kürşat GÜNTÜRK |
| Assistant(s) | |
| Aim | Develop artificial intelligence and computer vision applications in edge devices (Nvidia Jetson) |
| Course Content | This course contains; Introduction to Linux operating system,Installation of Nvidia Jetson Nano,Face detection application,Installation and use of CSI camera,Utilizing GPU functions of OpenCV,Optical flow and object detection applications,OpenCV DNN module applications,TensorRT model optimization and usage,Mediapipe application,Tesseract application,Nvidia Jetson GPIO usage,Semester project progress (I),Semester project progress (II),Project demo. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Develops artificial intelligence and computer vision applications in resource constraint platforms | 14 | F |
| Uses Nvidia Jetson platform | 14 | F |
| Teaching Methods: | 14: Self Study Method |
| Assessment Methods: | F: Project Task |
Course Outline
| Order | Subjects | Preliminary Work |
|---|
| 1 | Introduction to Linux operating system | |
| 2 | Installation of Nvidia Jetson Nano | |
| 3 | Face detection application | |
| 4 | Installation and use of CSI camera | |
| 5 | Utilizing GPU functions of OpenCV | |
| 6 | Optical flow and object detection applications | |
| 7 | OpenCV DNN module applications | |
| 8 | TensorRT model optimization and usage | |
| 9 | Mediapipe application | |
| 10 | Tesseract application | |
| 11 | Nvidia Jetson GPIO usage | |
| 12 | Semester project progress (I) | |
| 13 | Semester project progress (II) | |
| 14 | Project demo | |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications |
| No | Program Qualification | Contribution Level |
| 1 | 2 | 3 | 4 | 5 |
| 1 | 1. An ability to apply knowledge of mathematics, science, and engineering | | | | | |
| 2 | 2. An ability to identify, formulate, and solve engineering problems | | X | | | |
| 3 | 3. An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability | | | X | | |
| 4 | 4. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | | | X | | |
| 5 | 5. An ability to design and conduct experiments, as well as to analyze and interpret data | | X | | | |
| 6 | 6. An ability to function on multidisciplinary teams | | | | | |
| 7 | 7. An ability to communicate effectively | | | | X | |
| 8 | 8. A recognition of the need for, and an ability to engage in life-long learning | X | | | | |
| 9 | 9. An understanding of professional and ethical responsibility | | | | | |
| 10 | 10. A knowledge of contemporary issues | X | | | | |
| 11 | 11. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | | | | | |
Assessment Methods
| Contribution Level | Absolute Evaluation |
| Rate of Midterm Exam to Success | | 30 |
| Rate of Final Exam to Success | | 70 |
| Total | | 100 |
| ECTS / Workload Table |
| Activities | Number of | Duration(Hour) | Total Workload(Hour) |
| Course Hours | 0 | 0 | 0 |
| Guided Problem Solving | 0 | 0 | 0 |
| Resolution of Homework Problems and Submission as a Report | 0 | 0 | 0 |
| Term Project | 0 | 0 | 0 |
| Presentation of Project / Seminar | 0 | 0 | 0 |
| Quiz | 0 | 0 | 0 |
| Midterm Exam | 0 | 0 | 0 |
| General Exam | 0 | 0 | 0 |
| Performance Task, Maintenance Plan | 0 | 0 | 0 |
| Total Workload(Hour) | 0 |
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(0/30) | 0 |
| ECTS of the course: 30 hours of work is counted as 1 ECTS credit. |
Detail Informations of the Course
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|
| EMBEDDED ARTIFICIAL INTELLIGENCE and COMPUTER VISION | COE4215378 | Spring Semester | 2+2 | 3 | 6 |
| Course Program | Perşembe 17:30-18:15 Perşembe 18:30-19:15 Perşembe 19:30-20:15 Perşembe 20:30-21:15 |
| Prerequisites Courses | |
| Recommended Elective Courses | |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Elective |
| Course Coordinator | Prof.Dr. Bahadır Kürşat GÜNTÜRK |
| Name of Lecturer(s) | Prof.Dr. Bahadır Kürşat GÜNTÜRK |
| Assistant(s) | |
| Aim | Develop artificial intelligence and computer vision applications in edge devices (Nvidia Jetson) |
| Course Content | This course contains; Introduction to Linux operating system,Installation of Nvidia Jetson Nano,Face detection application,Installation and use of CSI camera,Utilizing GPU functions of OpenCV,Optical flow and object detection applications,OpenCV DNN module applications,TensorRT model optimization and usage,Mediapipe application,Tesseract application,Nvidia Jetson GPIO usage,Semester project progress (I),Semester project progress (II),Project demo. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Develops artificial intelligence and computer vision applications in resource constraint platforms | 14 | F |
| Uses Nvidia Jetson platform | 14 | F |
| Teaching Methods: | 14: Self Study Method |
| Assessment Methods: | F: Project Task |
Course Outline
| Order | Subjects | Preliminary Work |
|---|
| 1 | Introduction to Linux operating system | |
| 2 | Installation of Nvidia Jetson Nano | |
| 3 | Face detection application | |
| 4 | Installation and use of CSI camera | |
| 5 | Utilizing GPU functions of OpenCV | |
| 6 | Optical flow and object detection applications | |
| 7 | OpenCV DNN module applications | |
| 8 | TensorRT model optimization and usage | |
| 9 | Mediapipe application | |
| 10 | Tesseract application | |
| 11 | Nvidia Jetson GPIO usage | |
| 12 | Semester project progress (I) | |
| 13 | Semester project progress (II) | |
| 14 | Project demo | |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications |
| No | Program Qualification | Contribution Level |
| 1 | 2 | 3 | 4 | 5 |
| 1 | 1. An ability to apply knowledge of mathematics, science, and engineering | | | | | |
| 2 | 2. An ability to identify, formulate, and solve engineering problems | | X | | | |
| 3 | 3. An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability | | | X | | |
| 4 | 4. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | | | X | | |
| 5 | 5. An ability to design and conduct experiments, as well as to analyze and interpret data | | X | | | |
| 6 | 6. An ability to function on multidisciplinary teams | | | | | |
| 7 | 7. An ability to communicate effectively | | | | X | |
| 8 | 8. A recognition of the need for, and an ability to engage in life-long learning | X | | | | |
| 9 | 9. An understanding of professional and ethical responsibility | | | | | |
| 10 | 10. A knowledge of contemporary issues | X | | | | |
| 11 | 11. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | | | | | |
Assessment Methods
| Contribution Level | Absolute Evaluation |
| Rate of Midterm Exam to Success | | 30 |
| Rate of Final Exam to Success | | 70 |
| Total | | 100 |
Numerical Data
Ekleme Tarihi: 09/10/2023 - 10:50Son Güncelleme Tarihi: 09/10/2023 - 10:51
×- A-Z Programs
- Undergraduate
- Graduate
- Academic Calendar
- Double Major & Minor Programs
- Erasmus
- Prospective Students
- Registration
- Re-Enrolment
- Fees
- Directorate of Registrar’s Office
- FAQ
- Accommodation
- Scholarships
- Lateral and Vertical Transfer
- Summer School
- Preparation
- Transportation
