105 citations · 159 across the 9 of their papers we have counts for
11 papers
A comprehensive and trustworthy benchmark of AI methods for change detection in Earth observation
Tadej Tomanič, Alice Baudhuin, Jan Sotošek +4
Change detection in Earth observation (EO) is critical for monitoring land surface transformations, yet recent research in the field is constrained by inconsistent evaluation proto…
In-Domain Self-Supervised Learning Improves Remote Sensing Image Scene Classification
Ivica Dimitrovski, Ivan Kitanovski, Nikola Simidjievski +1
We investigate the utility of in-domain self-supervised pre-training of vision models in the analysis of remote sensing imagery. Self-supervised learning (SSL) has emerged as a pro…
Discover the Mysteries of the Maya: Selected Contributions from the Machine Learning Challenge & The Discovery Challenge Workshop at ECML PKDD 2021
Dragi Kocev, Nikola Simidjievski, Ana Kostovska +2
The volume contains selected contributions from the Machine Learning Challenge "Discover the Mysteries of the Maya", presented at the Discovery Challenge Track of The European Conf…
Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image Classification
Ivica Dimitrovski, Ivan Kitanovski, Dragi Kocev +1
We present AiTLAS: Benchmark Arena -- an open-source benchmark suite for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO). To…
AiTLAS: Artificial Intelligence Toolbox for Earth Observation
Ivica Dimitrovski, Ivan Kitanovski, Panče Panov +2
The AiTLAS toolbox (Artificial Intelligence Toolbox for Earth Observation) includes state-of-the-art machine learning methods for exploratory and predictive analysis of satellite i…
GalaxAI: Machine learning toolbox for interpretable analysis of spacecraft telemetry data
Ana Kostovska, Matej Petković, Tomaž Stepišnik +8
We present GalaxAI - a versatile machine learning toolbox for efficient and interpretable end-to-end analysis of spacecraft telemetry data. GalaxAI employs various machine learning…
Discovering outliers in the Mars Express thermal power consumption patterns
Matej Petković, Luke Lucas, Tomaž Stepišnik +3
The Mars Express (MEX) spacecraft has been orbiting Mars since 2004. The operators need to constantly monitor its behavior and handle sporadic deviations (outliers) from the expect…
Fuzzy Jaccard Index: A robust comparison of ordered lists
Matej Petković, Blaž Škrlj, Dragi Kocev +1
We propose Fuzzy Jaccard Index (FUJI) -- a scale-invariant score for assessment of the similarity between two ranked/ordered lists. FUJI improves upon the Jaccard index by incorpor…
Equation Discovery for Nonlinear System Identification
Nikola Simidjievski, Ljupčo Todorovski, Juš Kocijan +1
Equation discovery methods enable modelers to combine domain-specific knowledge and system identification to construct models most suitable for a selected modeling task. The method…
Machine learning for predicting thermal power consumption of the Mars Express Spacecraft
Matej Petković, Redouane Boumghar, Martin Breskvar +7
The thermal subsystem of the Mars Express (MEX) spacecraft keeps the on-board equipment within its pre-defined operating temperatures range. To plan and optimize the scientific ope…
Decoupling approximation robustly reconstructs directed dynamical networks
Nikola Simidjievski, Jovan Tanevski, Bernard Zenko +3
Methods for reconstructing the topology of complex networks from time-resolved observations of node dynamics are gaining relevance across scientific disciplines. Of biggest practic…