4 papers
AnomalyMatch: Discovering Rare Objects of Interest with Semi-supervised and Active Learning
Pablo Gómez, Laslo E. Ruhberg, Maria Teresa Nardone +1
Anomaly detection in large datasets is essential in astronomy and computer vision. However, due to a scarcity of labelled data, it is often infeasible to apply supervised methods t…
Cutana: A High-Performance Tool for Astronomical Image Cutout Generation at Petabyte Scale
Pablo Gómez, Laslo Erik Ruhberg, Kristin Anett Remmelgas +1
The Euclid Quick Data Release 1 (Q1) encompasses 30 million sources across 63.1 square degrees, marking the beginning of petabyte-scale data delivery through Data Release 1 (DR1) a…
MCTED: A Machine-Learning-Ready Dataset for Digital Elevation Model Generation From Mars Imagery
RafaŠOsadnik, Pablo Gómez, Eleni Bohacek +1
This work presents a new dataset for the Martian digital elevation model prediction task, ready for machine learning applications called MCTED. The dataset has been generated using…
Identifying Astrophysical Anomalies in 99.6 Million Cutouts from the Hubble Legacy Archive Using AnomalyMatch
David O'Ryan, Pablo Gómez
Astronomical archives contain vast quantities of unexplored data that potentially harbour rare and scientifically valuable cosmic phenomena. We leverage new semi-supervised methods…