Displaying 279 resources
Robot and Drone Swarms
This lecture overviews Robot and Drone Swarms that has many applications in autonomous systems: cars/drones.
Imitation Learning
This lecture overviews Imitation Learning (IL) that has many applications in Game Development, robotics training, Autonomous Driving and Computational Cinematography.
Introduction to Multiple Drone Systems
This lecture will provide the general context for this new and emerging topic, presenting the aims of multiple drone systems, focusing on their sensing and perception. Drone mission formalization, planning and control will be overviewed.
From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Survey
Keyphrase prediction aims to generate phrases (keyphrases) that highly summarizes a given document. Recently, researchers have conducted in-depth studies on this task from various perspectives.
High-Dynamic Range Imaging
This lecture overviews High-Dynamic Range Imaging that has many applications in digital photography.
Convolutional Neural Networks Lecture
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.
Digital Images and Videos
This lecture overviews various digital image types: 2D images, 3D images (videos, medical volumes, hyperspectral images). Multichannel images, e.g., colour and multispectral images and colour theory come next.
Privacy Protection, Ethics and Regulations for Autonomous Cars
This lecture overviews Privacy Protection, Ethics and Regulations that have many applications in Autonomous Cars.
e-Symposium 2023: A methodology for Forecasting Election results from Tweets
Social networks as the virtual equivalent of the ancient agora have become a preeminent space of political discourse. They can nurture new political trends and reveal existing ones.
Few Shot Object Recognition
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.
Active and Passive 3D shape reconstruction methods
This lecture overviews Active and Passive 3D shape reconstruction methods that has many applications in 3D computer vision, autonomous systems perception and medical imaging.