ADR Awareness Centre

This lecture overviews 3D Object Localization that has many applications in robotics and autonomous systems.

This lecture overviews Active and Passive 3D shape reconstruction methods that has many applications in 3D computer vision, autonomous systems perception and medical imaging.

This lecture overviews Kernel Methods that have many applications in classification and clustering. It covers the following topics in detail: Kernel Trick. Kernel Matrix. Kernel PCA. Kernel correlation and its use in object tracking. Kernel k-means.

This lecture overviews Domain Adaptation that has many applications in DNN training and adaptation.

This lecture overviews Computational Aesthetics  that has many applications in visual arts and computer graphics. It covers the following topics in detail: Neuroaesthetics. Computational Aesthetics. Critical problems in aesthetics.

This lecture overviews Few Shot Object Recognition that has many applications in image classification, when few training data are available.  It covers the following topics in detail: Few-shot Image Learning definitions and methods.

This lecture overviews various concepts related to multiple drone communications: LTE and WiFi communications, LTE communication infrastructure, IP network issues, Security analysis, throughput, latency and quality-of-service issues.

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.