Information Package / Course Catalogue
| Course Code | : YZO265 |
| Course Type | : Area Elective |
| Couse Group | : Short Cycle (Associate's Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 2 |
| Prt. | : 0 |
| Credit | : 2 |
| Lab | : 0 |
| ECTS | : 4 |
The objective of this course is to introduce students to the concept of computer vision, teach fundamental methods and techniques, and equip them with the fundamental knowledge and skills necessary for AI-enabled computer vision applications. Within the context of AI operations, the course focuses on practical applications such as object detection, image classification, and face recognition, as well as the effective use of computer vision in professional work processes.
The course begins with the definition and fundamental components of computer vision, covering the digital processing, analysis, and interpretation of images. It focuses on topics such as object detection, classification, segmentation, and facial recognition. The role of artificial intelligence algorithms in computer vision is explored, along with practical examples using popular tools such as OpenCV and TensorFlow. Data security, ethics, and professional standards are emphasized.
| 1. | Explains the concept of computer vision, its history and basic components. |
| 2. | Recognize the properties and formats of digital images and apply basic image processing techniques. |
| 3. | It applies image segmentation, edge detection and pattern recognition techniques in computer vision systems. |
| 4. | It uses artificial intelligence-supported methods in object detection and face recognition applications. |
| 5. | She follows current developments in the field of computer vision and artificial intelligence and attaches importance to lifelong learning. |
| 1. | ARTIFICIAL INTELLIGENCE AND COMPUTER VISION WITH PROJECTS Ümit AKSOYLU Kodlab |
| Type of Assessment | Count | Percent |
|---|---|---|
| Assignment | 1 | %10 |
| Quiz | 1 | %10 |
| Midterm Examination | 1 | %20 |
| Final Examination | 1 | %60 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 0 | 2 | 28 |
| Assignment | 1 | 16 | 1 | 17 |
| Quiz | 1 | 16 | 1 | 17 |
| Midterm Examination | 1 | 16 | 1 | 17 |
| Final Examination | 1 | 20 | 1 | 21 |
| TOTAL WORKLOAD (hours) | 100 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | PÇ-8 | PÇ-9 | PÇ-10 | PÇ-11 | PÇ-12 | |
OÇ-1 | 5 | 3 | 4 | 4 | 4 | 5 | 5 | 4 | 5 | 3 | 3 | 4 |
OÇ-2 | 5 | 5 | 5 | 4 | 4 | 5 | 4 | 5 | 4 | 2 | 3 | 4 |
OÇ-3 | 5 | 5 | 5 | 4 | 5 | 4 | 5 | 4 | 5 | 3 | 3 | 3 |
OÇ-4 | 5 | 5 | 5 | 4 | 4 | 4 | 4 | 5 | 4 | 2 | 2 | 3 |
OÇ-5 | 5 | 5 | 5 | 5 | 5 | 4 | 5 | 5 | 5 | 3 | 3 | 4 |