Seen all subjects? New data are released periodically, so check back often!
여기서 시작하기를 클릭하면 실제 연구를 할 수 있어요!
Zooniverse 토크
연구 팀 및 다른 자발적 참여자들과 이야기를 나누세요!
Artifact InSPECtor 통계
더 많은 통계 보기All Time Stats
Active Stats
모든 클릭은 의미가 있습니다! Artifact InSPECtor의 커뮤니티에 참가하여 이 프로젝트를 완료하고 연구자들이 중요한 결과를 낼 수 있게 도와주세요. '더 많은 통계 보기'를 클릭하면 더 많은 통계치를 볼 수 있습니다.
연구자의 메시지
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 InSPECtorArtifact InSPECtor 소개
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.