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A new experimental undergraduate course titled Computer Vision will be offered in Fall 2023.
ECE 49595CV
CRN: 24034
Instructor: Jeffrey Mark Siskind
Currently scheduled for: MWF 9:30am-10:20am in PHYS 111
The course will cover fundamentals of machine learning, image segmentation, object classification and localization, and activity classification and localization. Students will learn both how to use industry-standard tools such as PyTorch and how these tools work. The course satisfies the requirements of the AI concentration and AI minor. While, MyPurdue currently restricts enrollment to ECE, I will give overrides to anyone with the necessary background. Prerequisites include multivariate calculus (e.g. MA 261), linear algebra (e.g. MA 265), signal processing (e.g. ECE 301), probability (e.g. ECE 302), and programming ability (e.g. ECE 264 or ECE 20875) or equivalent with permission of instructor. Assessment will be based on programming homework and a group term programming project of the students’ choice. No exams. In the homework and term project, students will construct computer-vision systems that recognize objects, activities, or other things of interest in images and video.
