Introduction to visual data analysis
Introduction to visual data analysis - Lecture
Lecture resources (2018/2019):
- Part 01 - Linear filters
- Part 02 - Edges and gradients
- Part 03 - Features, Moravec and Harris corner detector, SIFT
- Part 04 - Artificial neural networks and deep learning
- Part 05 - Recent progress on Generative Adversarial Networks GANs
- Part 06 - Human Activity Recognition
Introduction to visual data analysis - Laboratory
Laboratory subjects:
- Part 01 - Image and Video Filtering
- Part 02 - Distance transform
- Part 03 - Optical Flow Estimation
- Part 04 - Neural Network
