Submitted keynotes abstracts are listed below.
Experts-based Recommendation System for Explainable Machine Learning methods in Data Science projects
In this poster, we discuss an interdisciplinary, open educational resource to provide help for Data Science researchers and...
Explainable Machine Learning based on Instances
Example-based explanation methods select particular instances of the dataset to explain the behavior of machine learning models or...
Trust through explainability: Technical and legal perspective
Explainability of an AI system is needed to build user's trust. However, explainability is not a feature that could be added to...
Needs of explainable AI in global healthcare challenges
The focus of this talk is today’s challenges of Artificial Intelligence in Medicine (AIM) and the need of explainability to...
Online explainability
The growing impact that artificial intelligence is having on our everyday lives, combined with the opaqueness of deep learning...
Operning the Black Box? - The European Legal Framework
Explainable AI (XAI) is not only relevant from the perspective of developers who want to understand how their system or model is...
Towards an explainable and convivial AI based tools: Illustration on medicine applications
Since 2010, the numerical Artificial Intelligence (AI) based on Machine Learning (ML) has produced impressive results, mainly in...
Explainable AI with Knowledge Graphs and Semantic Explanations
Semantic technologies, such as knowledge graphs, ontologies and reasoning have been developed as a bridge between human and...
Quality of data for computer vision algorithm
Focus on cognitive multimedia processing, open challenges and standard: Collecting "good" data for AI using AI Qualifying AI based...
Integrated modelling approaches to advance in the assessment of the impacts of plant protection products
Plant protection is a vital part of current agricultural and horticultural practices assuring yield and quality. Application of...
Explaining personalisation for a happier life: Recommender systems for wellbeing and leisure
This talk introduces the fundamentals of recommender systems as a data-driven AI tool for driving personalised user experiences...
Exploring Internal Representations and Extracting Rules from Deep Neural Networks
Artificial deep neural networks are a powerful tool, able to extract information from large datasets and, using this acquired...