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20212026
most citedThe BlackGEM telescope array I: Overview

33 citations · 95 across the 12 of their papers we have counts for

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9 papers · 1 filter

astro-ph.IM2026

SNID-SAGE: A Modern Framework for Interactive Supernova Classification and Spectral Analysis

Fiorenzo Stoppa, Stephen J. Smartt

We present SNID-SAGE (SuperNova IDentification-Spectral Analysis and Guided Exploration), a framework for supernova spectral classification with both a fully interactive graphical…

astro-ph.IM2024★ 14 cited

Automated Detection of Satellite Trails in Ground-Based Observations Using U-Net and Hough Transform

F. Stoppa, P. J. Groot, R. Stuik +4

The expansion of satellite constellations poses a significant challenge to optical ground-based astronomical observations, as satellite trails degrade observational data and compro…

astro-ph.IM2024★ 33 cited

The BlackGEM telescope array I: Overview

Paul J. Groot, S. Bloemen, P. Vreeswijk +75

The main science aim of the BlackGEM array is to detect optical counterparts to gravitational wave mergers. Additionally, the array will perform a set of synoptic surveys to detect…

astro-ph.IM2023★ 1 cited

FINKER: Frequency Identification through Nonparametric KErnel Regression in astronomical time series

F. Stoppa, C. Johnston, E. Cator +2

Optimal frequency identification in astronomical datasets is crucial for variable star studies, exoplanet detection, and asteroseismology. Traditional period-finding methods often…

astro-ph.IM2023★ 13 cited

AutoSourceID-Classifier. Star-Galaxy Classification using a Convolutional Neural Network with Spatial Information

F. Stoppa, S. Bhattacharyya, R. Ruiz de Austri +10

Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogues, a process susceptible to introducing inaccuracies, thereby potentially jeo…

astro-ph.IM2023★ 5 cited

AutoSourceID-FeatureExtractor. Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation

F. Stoppa, R. Ruiz de Austri, P. Vreeswijk +9

Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regress…