ADR Awareness Centre

Convolutional Neural Networks form the backbone of current AI revolution and are used in a multitude of classification and regression problems. This lecture overviews the transition from multilayer perceptrons to deep architectures.

In this lecture, the limitations of Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs) in effectively processing sequences are emphasized.

This lecture covers the basic concepts and architectures of Multi-Layer Perceptron (MLP), Activation functions, and Universal Approximation Theorem.

This lecture overviews MultiDrone Datasets that has many applications in autonomous drone research and development.

This lecture overviews Graph Convolutional Networks (GCN) that have many applications in Deep Learning, Signal and Video Analysis, Network Theory, Web Science and Social Media Analytics.

Privacy protection is a very important issue, in the context of social media and GDPR. This lecture overviews the face de-identification problem from an engineering perceptive.