https://micv.yonsei.ac.kr/courses/csi4116
[Course Outline]
Course Description
In this class, students will learn the basics of modern computer vision. The course will first cover low-level computer vision topics such as image filtering, edge detection, feature extraction, description and matching, grouping, and clustering. Then, we will cover high-level topics such as object detection, object recognition, segmentation, unsupervised learning, and generative models. We will cover recently popular techniques such as convolutional and recurrent neural networks. We will also discuss a few topics from recent computer vision conferences.
After the course, you may be able to:
Understand how machines see and understand photos and images
Have basic knowledge about some classic to modern computer vision techniques
See why and how modern computer vision techniques (e.g., deep learning) have evolved in such ways
Identify common pitfalls and mistakes ML/CV practitioners may make and learn how to avoid them
Identify or at least guess the family of ML/CV models that modern products could be using
Find an appropriate set of techniques and methods for the task of your interest
Start getting into advanced computer vision and deep learning techniques
Identify the subareas/topics in CV that interest you