This course provides a comprehensive introduction to state-of-the-art Intelligent Video Surveillance Systems, focusing on advanced computer vision and deep learning methodologies.

Outline of Lectures

1. Introduction to Machine Learning
2. Python, and Pytorch
3. Face Detection: Haar Feature and Adaboost
4. Bag of word and Part based Model Image Classification
5. Support Vector Machine
6. Loss Functions and Optimization: Gradient Decent
7. Convolutional Neural Networks
8. Training Neural Networks
9. Recurrent Neural Networks
10. Object Detection, Semantic Segmentation and Video Representation
11. Transformer Networks
12. Self-supervised Learning
13. Large Language Models