3 citations · 8 across the 11 of their papers we have counts for
12 papers
Deep Learning Super Resolution for Satellite Cloud Mask Downscaling
Angelos Georgakis, Valentina Kanaki, Giorgos Giannopoulos +4
A vast amount of optical satellite data is being transmitted to Earth-based servers every day, and more than half of this data is affected by haze or clouds. Additionally, this dat…
Review of Machine Learning Models for Solar Energetic Particle Prediction
Spiridon Kasapis, Pouya Hosseinzadeh, Kathryn Whitman +73
Solar energetic particle (SEP) events have attracted increasing attention due to their significant radiation hazards for aviation, spacecraft electronics, and human missions beyond…
HighFM: Towards a Foundation Model for Learning Representations from High-Frequency Earth Observation Data
Stella Girtsou, Konstantinos Alexis, Giorgos Giannopoulos +1
The increasing frequency and severity of climate related disasters have intensified the need for real time monitoring, early warning, and informed decision-making. Earth Observatio…
Distilling Vision Transformers for Distortion-Robust Representation Learning
Konstantinos Alexis, Giorgos Giannopoulos, Dimitrios Gunopulos
Self-supervised learning has achieved remarkable success in learning visual representations from clean data, yet remains challenging when clean observations are sparse or not avail…
GLANCE: Global Actions in a Nutshell for Counterfactual Explainability
Loukas Kavouras, Eleni Psaroudaki, Konstantinos Tsopelas +9
The widespread deployment of machine learning systems in critical real-world decision-making applications has highlighted the urgent need for counterfactual explainability methods…
Fairness in AI: challenges in bridging the gap between algorithms and law
Giorgos Giannopoulos, Maria Psalla, Loukas Kavouras +4
In this paper we examine algorithmic fairness from the perspective of law aiming to identify best practices and strategies for the specification and adoption of fairness definition…
FALE: Fairness-Aware ALE Plots for Auditing Bias in Subgroups
Giorgos Giannopoulos, Dimitris Sacharidis, Nikolas Theologitis +2
Fairness is steadily becoming a crucial requirement of Machine Learning (ML) systems. A particularly important notion is subgroup fairness, i.e., fairness in subgroups of individua…
Next day fire prediction via semantic segmentation
Konstantinos Alexis, Stella Girtsou, Alexis Apostolakis +2
In this paper we present a deep learning pipeline for next day fire prediction. The next day fire prediction task consists in learning models that receive as input the available in…
Fairness Aware Counterfactuals for Subgroups
Loukas Kavouras, Konstantinos Tsopelas, Giorgos Giannopoulos +6
In this work, we present Fairness Aware Counterfactuals for Subgroups (FACTS), a framework for auditing subgroup fairness through counterfactual explanations. We start with revisit…
Auditing for Spatial Fairness
Dimitris Sacharidis, Giorgos Giannopoulos, George Papastefanatos +1
This paper studies algorithmic fairness when the protected attribute is location. To handle protected attributes that are continuous, such as age or income, the standard approach i…
Data-driven soiling detection in PV modules
Alexandros Kalimeris, Ioannis Psarros, Giorgos Giannopoulos +3
Soiling is the accumulation of dirt in solar panels which leads to a decreasing trend in solar energy yield and may be the cause of vast revenue losses. The effect of soiling can b…
Simplifying Impact Prediction for Scientific Articles
Thanasis Vergoulis, Ilias Kanellos, Giorgos Giannopoulos +1
Estimating the expected impact of an article is valuable for various applications (e.g., article/cooperator recommendation). Most existing approaches attempt to predict the exact n…