Computer Vision

Info
290T

3 units

Course Description

This course introduces the theoretical and practical aspects of computer vision, covering both classical and state of the art deep-learning based approaches. This course covers everything from the basics of the image formation process in digital cameras and biological systems, through a mathematical and practical treatment of basic image processing, space/frequency representations, classical computer vision techniques for making 3D measurements from images, and modern deep-learning based techniques for image classification and recognition.

Prerequisites

Linear algebra and Python (INFO 206A & B or equivalent).

Requirements Satisfied

MIMS: Technology Requirement
Last updated: July 6, 2022