Akademik Dersler - Tanıtım

Last Updated: 23/06/2026

Code - Course Title	Course Type	Laboratory + Practice	ECTS
BVA228 - Computer Vision	IV. SEMESTER	2 +1	3.0

Language of Instruction	Türkçe
Course Type	Area Elective Courses
Course Instructor(s)	ÖĞR. GÖR. AHMET MÜCAHİD ARVASİ
Mode of Delivery	Face to face
Place of Delivery
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Prerequisites	There are no prerequisites or corequisites for this course.
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Aims of the Course

Weeks	Learning Outcomes	Topics	Teaching Methods
Week - 1		Fundamentals of Computer Vision: Image Formation, Pixels, and Color Spaces (RGB, HSV, Grayscale)
Week - 2		Basic Filtering Operations: Image Smoothing, Noise Reduction, and Spatial Filters
Week - 3		Image Processing Techniques 1: Gradients and Edge Detection Algorithms (Sobel, Canny)
Week - 4		Image Processing Techniques 2: Morphological Operations (Erosion, Dilation) and Image Segmentation
Week - 5		Feature Extraction: SIFT, SURF, and Harris Corner Detection Techniques
Week - 6		Relationships Between Images: Feature Matching and Fundamentals of Object Recognition
Week - 7		Deep Learning in Computer Vision: Introduction to Convolutional Neural Networks (CNN) and Feature Learning
Week - 8		Midterm Exam
Week - 9		Modern CNN Architectural Designs (ResNet, VGG) and Transfer Learning in Image Classification
Week - 10		Object Detection: R-CNN Based Region Networks and YOLO Architectures
Week - 11		Real-Time Object Tracking and Optical Flow Algorithms
Week - 12		Biometric Analysis Applications: Face Recognition and Human Pose Estimation
Week - 13		Industrial Applications: Environmental Perception in Autonomous Systems and Video Analytics
Week - 14		Computing on Edge Devices for Vision, Model Optimization, and End-of-Term Project Presentations

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Assessment Method and Passing Requirements
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