Laboratory Classes

Week Topic Handouts
1. Introduction -
2. Least Mean Squares Line Fitting .zip
3. RANSAC – fitting a line to a set of points .zip
4. Hough Transform for line detection .zip
5. Distance Transform (DT). Pattern Matching using DT .zip
6. Probability Density Estimation .zip
7. K-Means Clustering .zip
8. Principal Component Analysis .zip
9. K-Nearest Neighbor Classifier .zip
10. Naïve Bayes Classifier: Simple Digit Recognition Application .zip
11. Linear classifiers. Perceptron algorithm .zip
12. Adabost with Decision Stumps .zip
13. Support Vector Machine .zip
14. Lab Assessment -


Each lab session can end with a homework for the next session.


None for the moment.