YSC3221 Computer Vision and Deep Learning

Semester 2, 2017/2018
Yale-NUS College





Description:

Images and videos are everywhere. Using your mobile phone, it becomes easy to snap a picture or to record video. Yet, how can we automatically extract the rich visual information from those images/videos? This is the task computer vision attempts to solve. The goal of computer vision is to make computers work like human visual perception, namely, to understand and recognize the world through visual data. One important technique in computer vision is deep learning. Deep learning is able to extract features and to infer the visual information from the features automatically and accurately. This course will focus on the fundamentals of deep learning and its applications to computer vision.


Prerequisite: Programming skill in python, and maths (linear algebra, calculus, statistics/probability).
Textbook:
  1. Computer Vision: Models, Learning, and Inference, by S.J.D. Prince.
  2. Deep Learning, by Ian Goodfellow and Yoshua Bengio and Aaron Courville
The ebook versions are accessible through NUS library. Note, we will use the books loosely (some, if not many, topics are taken from other sources).
Instructor: Robby T. Tan (robby.tan [att] yale-nus.edu.sg)


Syllabus: