ADR Awareness Centre

The technical report presents popular methods for mapping data into a low-dimensional manifold (nonlinear dimensionality reduction).

This lecture overviews the topics of continuous-time periodic signals, signal frequencies and Fourier Transform (FT).  Its relation to Laplace transform is presented.

This lecture overviews the relation between matter and system complexity on one hand and Life, Intelligence and Environment on the other one. First the theoretical tools (systems, graph and  network theory) are overviewed.

Recently, Convolutional Neural Networks (CNNs) have been used for object/target (e.g., face, person, car, pedestrian, road sign) detection with great results.

This lecture overviews Spectral Signal Analysis that has many applications in periodicity estimation and acoustic/speech/music/biomedical signa analysis.

This resource provides links to representative repositories of 3D faces. In the last few years, some 3D face datasets have been acquired and made publicly available. Typically, these datasets have been designed targeting a specific application.

Self-awareness is a broad concept borrowed from cognitive science and psychology that describes the property of a system, which has knowledge of “itself,” based on its own senses and internal models.

This lecture overviews Explainable AI that has many applications in trustworthy AI systems and autonomous systems.

This lecture overviews Crowd Detection and Analysis that has many applications in Human-centered Computing, Image and Video Analysis and Smart City applications and surveillance. It covers the following topics in detail: Pedestrian Detection.

This resource corresponds to 3rd video from the AI Excellence Lecture Series. Explore the complexities of bias in artificial intelligence as experts present innovative experimental approaches to assess and mitigate bias in face recognition and analy

This book provides an introduction to the theory of manifolds in an easy readable way. Key concepts of manifolds, angent spaces and Lie group / Lie algebra are presented.

This lecture overviews Deep Autoencoders that has many applications in image denoising, classification, generation and in object pose estimation.