Computer Vision
An introduction to basic concepts and techniques in computer vision. Topics include low-level operations such as image filtering, correlation, edge detection and Fourier analysis. Image segmentation, texture and color analysis. Perspective, cameras and 3D reconstruction of scenes using stereo and structure from motion. Deep learning for object detection, recognition and classification in images and video.
Topics
- low-level operations such as image filtering
- correlation
- edge detection and Fourier analysis
Topics explicitly listed in official catalogue description
Prerequisites & course information
Prerequisite: BIOI603 , DATA603 , or MSML603 . Cross-listed with: MSML640 , MSAI640 . Restriction: Must be in one of the following in-person or online programs: MS in Data Science; MS in Applied Machine Learning; or Ms in Artificial Intelligence; and must have 12 graduate level credits in program. Credit Only Granted for: MSML640 , MSAI640 or DATA640 .
Sources
- Course catalogue ↗2026-2027