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Możesz prowadzić prawdziwe badania. Wystarczy kliknąć tutaj, aby rozpocząć!
Porozmawiaj z zespołem badawczym i innymi wolontariuszami!
Liczy się każde kliknięcie! Dołącz do społeczności projektu Artifact InSPECtor, aby uczestniczyć w jego realizacji i pomóc badaczom w uzyskaniu ważnych wyników. Kliknij przycisk „Pokaż więcej statystyk”, aby poznać jeszcze więcej danych statystycznych.
Your work to identify artifacts tells us which data to keep for scientific analysis. Improving our machine learning model to identify artifacts through your classifications enables us to hit the ground running with the new Roman Space Telescope!
Artifact InSPECtorSpace telescope data contains both astronomical objects and artifacts. As you can imagine, we need to know what is an artifact so we know what data to ignore during analysis. This is especially important with data from new telescopes (like Euclid and Roman) since we aren’t familiar with the artifacts yet.
We use a machine learning model to recognize these artifacts, but it isn’t perfect. Your job is to determine if the data is showing an artifact, and if our model recognized it correctly. In the future, we will use this model, improved with your classifications, to determine which data to keep and which to throw out.
This work is funded by NASA. Learn more about NASA Citizen Science Projects here: science.nasa.gov/citizenscience.
This project makes use of Q1 data from European Space Agency's Euclid mission; learn more here: cosmos.esa.int/web/euclid/euclid-q1-data-release
ELSA: Euclid Legacy Science Advanced analysis tools (Grant Agreement no. 101135203) is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Innovate UK. Neither the European Union nor the granting authority can be held responsible for them. UK participation is funded through the UK Horizon guarantee scheme under Innovate UK grant 10093177.