ADR Awareness Centre

This lecture overviews 1D Convolutional Neural Networks that has many applications in 1D signal analysis.

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.

This lecture overviews Decision Surfaces and, in particular, Support Vector Machines that have many applications in Machine Learning and Pattern Recognition. It covers the following topics in detail: Decision surfaces. Hyperplanes.

This lecture overviews Label Propagation that has many applications in pattern recognition (semi-supervised learning) and in the study of diffusion processes.

This lecture overviews Data Clustering  that has many applications in e.g., facial image clustering, signal/image clustering, concept creation.  It covers the following topics in detail: Clustering Definitions.

This lecture overviews Distance-based Classification that has many applications in classification.

This lecture overviews human-centric AI methods that can be utilized to facilitate visual interaction between humans and autonomous vehicles (e.g., through gestures captured by RGB cameras), in order to ensure their safe and successful cooperation