Displaying 204 resources
Video Quality
This lecture overviews Video Quality that has many applications in cinema movies, digital TV and video streaming. It covers the following topics in detail: Video Quality Assessment Methods.
Computational Geometry
This lecture overviews Computational Geometry that has many applications in Computer Graphics, Robotics, Geographic Information Systems, CAD/CAM.
Privacy Protection, Ethics and Regulations for Autonomous Cars
This lecture overviews Privacy Protection, Ethics and Regulations that have many applications in Autonomous Cars.
Introduction to 2D Computer Vision
This lecture overviews digital images and 2D Computer Vision (image analysis).
Imitation Learning
This lecture overviews Imitation Learning (IL) that has many applications in Game Development, robotics training, Autonomous Driving and Computational Cinematography.
Hidden Markov Models
This lecture overviews Hidden Markov Models that have many applications in Data Analytics and Signal Analysis. It covers the following topics in detail: Markov Chains. Hidden Markov Chains: Viterbi algorithm, Forward-backward algorithm.
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.
Dynastic Potential Crossover Operator
An optimal recombination operator for two-parent solutions provides the best solution among those that take the value for each variable from one of the parents (gene transmission property).
Robot and Drone Swarms
This lecture overviews Robot and Drone Swarms that has many applications in autonomous systems: cars/drones.
Symbolic, Statistical, and Causal Representations
In machine learning, we use data to automatically find dependencies in the world, with the goal of predicting future observations.
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.
Data Clustering
This lecture overviews Data Clustering that has many applications in e.g., facial image clustering, signal/image clustering, concept creation. It covers the following topics in detail: Clustering Definitions.