ADR Awareness Centre

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.

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.

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

This lecture overviews Human Centered Computing that has many applications in Human-Computer Interfaces, Data Analytics and Social Media Analytics. It covers the following topics in detail: Semantic Video Content Analysis.

This lecture overviews Face Detection that has many applications in Human-centered Computing, Image and Video Analysis and Social Media Analytics. It covers the following topics in detail: Face Detection definition: Regression and Classification.