ADR Awareness Centre

This lecture overviews Autonomous Car Sensors that has many applications in autonomous car perception.

This lecture overviews Video Streaming  that has many applications in videoconferencing, social media and TV webcasting.

This lecture overviews Transform Video Compression  that has many applications in digital TV broadcasting, videoconferencing, video streaming and social media.

This lecture overviews Multiple Drone Media Production that has many applications in drone cinematography.

This lecture overviews Image-Based Rendering and View Synthesis that has many applications in computer graphics, data visualization, simulators, Virtual Environments and media production.

This lecture overviews Recurrent Neural Networks and Long Short-Term Memory (LSTM) networks that have many applications in signal and video analysis. It covers the following topics in detail: Neural Networks for Sequence Analysis.

This lecture overviews Image Formation, which is of primary importance in ensuring image quality and enabling image processing. It covers the following topics in detail: Light reflection models. Camera structure and models, e.g., Pinhole Camera.

This lecture overviews an important topic of Digital Humanities, namely digital painting analysis that has many applications in painting conservation and in the history of arts.

This lecture overviews Deep Reinforcement Learning that has many applications in, e.g., Game playing agents, Self-driving vehicles, Robotics (Robot cleaners) and Stock exchange agents.

This lecture overviews Distance-based Classification that has many applications in classification. It covers the following topics in detail: k-Nearest neighbor classification, Nearest neighbor graphs Supervised Learning Vector Quantization, LVQ1/2/3.

This lecture overviews Neural SLAM   that has many applications in robotic and autonomous vehicle localization and mapping.

Motion estimation principals will be analyzed. Initiating form 2D and 3D motion models, displacement estimation as well as quality metrics for motion estimation will subsequently be detailed.