Training Information

• Software developers, engineers, technical students
• Those involved in AI / ML / Robotics projects
• Professionals working in visual product processing, media, security, healthcare, agriculture
• Those wanting integration of drone/robot control training with image processing
• University students, researchers

• Basic programming knowledge (Python preferred)
• Basic mathematics: Linear algebra, probability, statistics
• Preparatory Course recommended for those unfamiliar with fundamentals of Image Processing / Computer Vision
• Computer with sufficient hardware (GPU optional, simulation possible)
• Basic knowledge of image processing / visual data libraries if needed

Curriculum

• What is a digital image, pixel, color space (RGB, HSV, grayscale), bit depth
• Image sources & formats
• Practice: Loading, displaying, color conversions

• Convolution, low/high-pass filters
• Noise types (Gaussian, Salt-&-Pepper)
• Practice: Adding and removing noise, filter comparison

• Sobel, Canny edge detectors; Hough transforms
• Basic segmentation (thresholding, region-based)
• Practice: Edge detection, segmentation applications

• Image scaling, rotation, perspective transformation
• Image alignment, warping
• Practice: Transformation and alignment exercises

• Histograms, color distribution, contrast/brightness adjustment
• Visualization techniques
• Project: Quality control / enhancement on an image dataset

• SIFT, SURF, ORB methods
• Feature matching
• Practice: Creating a panorama

• CNN architectures, transfer learning
• Practice: Classification with a pretrained model

• Object detection concepts (YOLO, SSD, Faster R-CNN)
• Semantic & instance segmentation
• Practice: Object detection and masking applications

• Optical flow, video frame analysis
• Tracking, motion prediction
• Practice: Motion detection on video

• Image content and privacy (KVKK, GDPR, etc.)
• Ethical use, copyrights, security
• Project: Application presentation based on participants’ chosen field

Training Outcomes

• Participants understand image representation and basic processing techniques
• They apply filtering, edge detection, segmentation
• They perform classification and object detection with deep learning models
• They conduct video and motion analysis
• They gain awareness of image processing and data privacy

Training Notes

• The instructor may adjust duration and content based on participant profile.
• Local regulations on image usage, privacy and personal data protection (KVKK, GDPR) are detailed.
• Tools (OpenCV, TensorFlow, PyTorch, etc.) are selected based on infrastructure suitability.
• Participants lacking fundamentals (programming, math / linear algebra) are directed to preparatory courses.
• Participants earn a university or institution-approved certificate upon completion.