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 overviews Graph Neural Networks that has many applications in Deep Learning, Signal and Video Analysis, Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Introduction to Graphs.

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 Natural Language Processing (NLP) that has many applications in text analytics, Linguistics, Machine translation and sentiment analysis.

This lecture overviews Neural Speech Recognition is a special case of Automatic Speech Recognition (ASR), i.e., the transcription of speech to text that has many applications e.g., in call centers, dictation, meeting minutes creation, Smart assist