Seen all subjects? New data are released periodically, so check back often!
您可以點按此處開始真正的研究！
Zooniverse 討論區
與研究團隊和其他志願者交談！
Artifact InSPECtor 統計資料
檢視更多統計資料All Time Stats
Active Stats
每次點按皆計數！加入 Artifact InSPECtor 的社群，完成此專案，協助研究人員產出重要成果。點按「檢視更多統計資料」來查看更多統計資料。
來自研究人員的訊息
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 InSPECtor關於 Artifact InSPECtor
Space 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.