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Semantic Segmentation of Solar Radio Spikes at Low Frequencies: SpikeNet Data Samples

Friday 8 March 2024, by Baptiste Cecconi

This dataset provides a data sample produced by SpikeNet, as described in Semantic Segmentation of Solar Radio Spikes at Low Frequencies, submitted to The Open Journal of Astrophysics.

Link to data repository

The data is also accessible using virtual observatory interfaces on http://vogate.obs-nancay.fr:

  • solar_nenufar_ml.epn_core: table (VESPA compliant);
  • solar_nenufar_ml.spikenet_predictions: individual TFCat features.


This dataset contains the result of the SpikeNet pipeline for a few minutes of NenuFAR data obtained on 2024-01-20.

The data is available in the TFCat format [Cecconi, et al. 2023]

Coverage and sampling

  • Target: the Sun
  • Time range: 2024-01-20 12:01 to 12:51
  • Spectral range: 18.46 to 54.67 MHz


This work has been supported by the Europlanet-2024 Research Infrastructure project, which received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871149 and a grant from Paris Observatory science council under the MINERVA project.
We acknowledge the use of the Nançay Data Center (CDN – Centre de Données de Nançay) facility. The CDN is hosted by the Observatoire Radioastronomique de Nançay (ORN) in partnership with the Observatoire de Paris, the Université d’Orléans, the Observatoire des Sciences de l’Univers d’Orléans (OSUC) and the French Centre National de la Recherche Scientifique (CNRS). The CDN is supported by the Région Centre-Val de Loire (département du Cher). The ORN is operated by the Observatoire de Paris, associated with the CNRS.
The research leading to these results has received funding from the European Union’s Horizon Europe Programme under the EXTRACT Project, grant agreement n° 101093110.


Any question or request should be addressed to contact.maser@obspm.fr


  • Cecconi, B., Louis, C. K., Bonnin, X., Loh, A. & Taylor, M. B. (2023). Time-frequency catalogue: JSON implementation and python library. Frontiers Astronomy Space Sci 9, 1049677. doi:10.3389/fspas.2022.1049677

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