Machine Intelligence - Lecture 5 (Computer Vision, Features, Fisher Vector, VLAD)

SYDE 522 – Machine Intelligence (Winter 2019, University of Waterloo)

Target Audience: Senior Undergraduate Engineering Students


Course Outline - The objective of this course is to introduce the students to the main concepts of machine intelligence as parts of a broader framework of “artificial intelligence”. An overview of different learning, inference and optimization schemes will be provided, including Principal Component Analysis, Support Vector Machines, Self-Organizing Maps, Decision Trees, Backpropagation Networks, Autoencoders, Convolutional Networks, Fuzzy Inferencing, Bayesian Inferencing, Evolutionary algorithms, and Ant Colonies.

Lecture 5 - Computer Vision (Features, Fisher Vector, VLAD)

[dummy_ani]

The professor is so good and explains with such interest and humor....I haven't seen teachers make half as many expressions as him

[thgreenbeast]

My university's professor just runs through some slides and I never understand a thing. I like how this guy writes everything out.

[sylvietud]

Many thanks for sharing this video. The professor is brilliant at explaining and sharing his knowledge.

[MrQqqq]

I have to thank you again for your teaching techniques. I am following your lecture 5 and i start to understand the process of AI. A want to send you a very big message for all your efforts. Thanks thanks thanks...

[houssemeddine]

anyone is watching this lecture with x2 speed :D