ADR Awareness Centre

This lecture overviews Bayesian Learning that has many applications in pattern recognition and clustering. It covers the following topics in detail: Bayes probability theorem. Bayes decision rule. Bayesian classification.

This lecture overviews Parameter estimation that has many applications in Statistics and Pattern Recognition.

This lecture overviews Hypothesis Testing that has many applications in statistics and pattern recognition.

This lecture overviews Kernel Methods that have many applications in classification and clustering. It covers the following topics in detail: Kernel Trick. Kernel Matrix. Kernel PCA. Kernel correlation and its use in object tracking.

This lecture overviews Dimensionality Reduction that has many applications in object clusring and object recognition.  It covers the following topics in detail: Feature selection. Principal Component Analysis. Linear Discriminant Analysis.

This lecture overviews Graph-Based Pattern Recognition that has many applications in data clustering and dimensionality reduction.