Abstract
Focus on cognitive multimedia processing, open challenges and standard:
- Collecting "good" data for AI using AI
- Qualifying AI based computer vision in real life scenario
Susana Ladra- University of A Coruña
In the field of algorithms and data structures analysis and design, most of the researchers focus only on the space/time trade-off...
Georges Quénot- LIG-CNRS
The performance of deep Convolutional Neural Networks (CNN) has been reaching or even exceeding the human level on large number of...
Sima Sinaei- Malardalen University
Deep Neural Networks (DNNs) suffer from energy-hungry implementation due to their computation and memory intensive processing...
Marcin Pietron- University of Science and Technology in Cracow
The performance of AI systems based on deep learning models is exceeding the human level on an increasing number of tasks like...
Isaac Martin- DSLAB. Data Science Lab. University Rey Juan Carlos
Example-based explanation methods select particular instances of the dataset to explain the behavior of machine learning models or...
Agnes Delaborde- LNE - Laboratoire national de métrologie et d'essais
European regulations require that products marketed in the territory must be safe and reliable. In this context, it is necessary...
Nelly Bencomo- Aston University
On the one hand, there has been a growing interest towards the application of AI-based for self-adaptation under uncertainty. On...
Nelly Bencomo- Aston University
On the one hand, there has been a growing interest towards the application of AI-based for self-adaptation under uncertainty. On...
Juan Carlos Augusto- Middlesex University London
We highlight the infrastructure available in our Smart Spaces lab, the projects which have been run with it, as well as other...
Mario Pichler- Software Competence Center Hagenberg GmbH
The freshwater resources have been constantly depleting worldwide and it is forecasted that several countries will face acute...
Atakan Aral- Vienna University of Technology
Analysis of environmental data is the key to most computational approaches for sustainability. However, such data feature complex...
Alsayed Algergawy- Heinz-Nixdorf Chair for Distributed Information Systems at the University of Jena
The biodiversity research discipline studies the totality and variability of organisms, their morphology and genetics, life...
Josef Spillner- Zurich University of Applied Sciences, SPLab
Data-driven environmental sustainability should consider not just getting more data, but smarter representation of data. Today's...
Slobodan Lukovic- University of Lugano
Given the increased dynamism and complexity of modern world, researchers struggle to cope to exploit as much as possible...
Wei Wang- University of Skövde
Benefiting from the advancement of information and communication technology, more and more data related to product manufacturing...
Marcin Pietron- University of Science and Technology in Cracow
The performance of AI systems based on deep learning models is exceeding the human level on an increasing number of tasks like...
Georges Quénot- LIG-CNRS
The performance of deep Convolutional Neural Networks (CNN) has been reaching or even exceeding the human level on large number of...
Mario Pichler- Software Competence Center Hagenberg GmbH
Interpretability of artificial intelligence (AI) models is one of the most discussed topics in contemporary AI research (Holm...
Salvador Abreu- University of Evora
Declarative methods for combinatorial optimisation (such as modeling as a CSP) can form the basis of highly scalable solvers...
Kyle Martin- Robert Gordon University
Organisations face growing legal and social responsibilities to be able to explain decisions they have made using autonomous...
Florian Kammueller- Middlesex University London
Successful Intrusion Detection systems heavily rely on machine learning to detect anomaly. However, particularly in 5G networks...
Andras Pataricza- Budapest University of Technology and Economics
Physical and technical systems are peculiar for machine learning.The solution of a variety of engineering problems necessitates...
Jan Ramon- Inria
Explainability has been investigated in several ways in the field of machine learning: there are more interpretable models (e.g...
Arun Kumar Singh- University of Tartu
End to end deep learning of control policies have gathered much attention in recent times. Their attractiveness stems from the...
Isaac Martin- DSLAB. Data Science Lab. University Rey Juan Carlos
In this poster, we discuss an interdisciplinary, open educational resource to provide help for Data Science researchers and...
Isaac Martin- DSLAB. Data Science Lab. University Rey Juan Carlos
Example-based explanation methods select particular instances of the dataset to explain the behavior of machine learning models or...
Grzegorz J. Nalepa- Jagiellonian University, AGH University
Explainability of an AI system is needed to build user's trust. However, explainability is not a feature that could be added to...
Jose M. Juarez- University of Murcia
The focus of this talk is today’s challenges of Artificial Intelligence in Medicine (AIM) and the need of explainability to...
Andrea Passerini- University of Trento
The growing impact that artificial intelligence is having on our everyday lives, combined with the opaqueness of deep learning...
Martin Ebers- University of Tartu, School of Law
Explainable AI (XAI) is not only relevant from the perspective of developers who want to understand how their system or model is...
Christophe Denis- Sorbonne University
Since 2010, the numerical Artificial Intelligence (AI) based on Machine Learning (ML) has produced impressive results, mainly in...
Agnieszka Lawrynowicz- Poznan University of Technology
Semantic technologies, such as knowledge graphs, ontologies and reasoning have been developed as a bridge between human and...
Pieter Verboven- KU Leuven - University of Leuven
Plant protection is a vital part of current agricultural and horticultural practices assuring yield and quality. Application of...
Ivan Palomares Carrascosa- University of Bristol
This talk introduces the fundamentals of recommender systems as a data-driven AI tool for driving personalised user experiences...
Carlos Peña-Reyes- Swiss Institute of Bioinformatics (SIB)
Artificial deep neural networks are a powerful tool, able to extract information from large datasets and, using this acquired...
Peter Challenor- University of Exeter
Environmental science has developed to the stage where there are simulators (numerical models), often involving the solutions of...
Carola-Bibiane Schönlieb- University of Cambridge
In this talk we discuss the idea of data-driven regularisers for inverse imaging problems. We are in particular interested in the...
Jose M. Such- King's College London
With the widespread and pervasive use of AI for automated decision-making systems, AI bias is becoming more apparent and...