


2D Systems
This lecture overviews 2D Systems, as they are the primary tools for many image processing and analysis operations. It covers the following topics in detail: Two-Dimensional Discrete LTI Systems. 2D convolutions. 2D correlation.



Digital Images
This lecture overviews digital image coordinate systems and their mathematical representations (vectors, matrices). Memory allocation issues are presented.



Image Sampling
This lecture overviews spatial image frequency content and image sampling. Rectangular and hexagonal sampling grids are presented. Sampled image frequency content is analyzed and a 2D version of Shannon theorem is presented.


The Ordinal Nature of Affect: An Emerging Approach
Computational representation of everyday emotional states is a challenging task and, arguably, one of the most fundamental for affective computing.


Experience Driven Content Generation
Procedural content generation (PCG) is an increasingly important area of technology within modern human-computer interaction (HCI) design.

Artificial Intelligence and Games Textbook
This book aims to be the first comprehensive textbook on the application and use of artificial intelligence (AI) in, and for, games.



Stereotypes in Language & Computational Language Models
Combined knowledge from linguistics, psychology, and natural language processing.



Understanding and mitigating bias in AI automated systems
“The AI community has been focusing on developing fixes for harmful bias and discrimination, through so-called ‘debiasing algorithms’ that either try to fix data for known or expected biases, or constrain the outcomes of a given predictive model t



Deep Autoencoders
This lecture overviews Deep Autoencoders that has many applications in image denoising, classification, generation and in object pose estimation.

Digital libraries for 3D human face
This resource provides links to representative repositories of 3D faces. In the last few years, some 3D face datasets have been acquired and made publicly available. Typically, these datasets have been designed targeting a specific application.



Artificial Neural Networks. Perceptron
This lecture will cover the basic concepts of Artificial Neural Networks (ANNs): Biological neural models, Perceptron, Activation functions, Loss types, Steepest Gradient Descent, On-line Perceptron training, Batch Perceptron training.



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.