Lectures: Thursdays 12:30-14:30, Ullman 707
Tutorials: Thursdays 14:30-15:30, Ullman 707
This is an introductory level course in Computer Vision, which describes basics and common techniques and algorithms and some recent deep-learning based methods. The Homework include hands-on experience with some problems and algorithms.
A passing grade in an Image Processing course is required. Recommended such courses are "Signal and Image Processing by Computer" (236327) or "Image Processing and Analysis" (046200). Students without the prerequisite must first receive the lecturer's agreement to participate in the course, and participate in a basic image processing crash course (including one additional HW assignment) in the beginning of the semester.
Grading Policy: Four equally weighted homework assignments (40%). Final exam (60%).
You are allowed to submit HW in pairs.
This is not mandatory- submissions of individuals are fine as well.