Displaying 273 resources
Genomic Signal Analysis
This lecture overviews Genomic Signal Analysis that has many applications in Bioinformatics, Biology and Medicine. It covers the following topics in detail: DSP Algorithms for Genomic Sequences.
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.
AI Studies
AI is a rapidly emerging field that has opened up new vistas of innovation and creativity. From intelligent systems to self-driving cars, AI has transformed the way we live and work.
High-Dynamic Range Imaging
This lecture overviews High-Dynamic Range Imaging that has many applications in digital photography.
Transfer Learning
This lecture overviews Transfer Learning (TL) that has many applications in DNN training and adaptation, Image Understanding, Text Mining, Activity Recognition, Bioinformatics, Transportation.