[Other] Building and verifying end-to-end deep learning engines to detect anomalies in spacecraft telemetry using satellite digital twins

Youssef_Mus Post time 1 hour(s) ago | Show all posts |Read mode

This post will be closed automatically in 2026-07-15 04:47

Reward30points

  title={Building and verifying end-to-end deep learning engines to detect anomalies in spacecraft telemetry using satellite digital twins},
  year={2022},
  journal={Proceedings of the International Astronautical Congress, IAC},
  author={Nalepa, J. and Andrzejewski, J. and Myller, M. and Kiesbye, J. and Messmann, D. and Koch, J. and Kostrzewa, D.},
  url={https://dl.iafastro.directory/event/IAC-2022/paper/71909/},
  keywords={anomaly detection, deep learning, digital twin, LSTM, MOVE-II, on-board processing},

You can support us by donating, we would be very grateful.

Reply

Use magic Donate Report

All Reply0 Show all posts

Reply

Youssef_Mus Lv.2

Junior Member

post
reply
points
185

[Other] Building and verifying end-to-end deep learning engines to detect anomalies in spacecraft telemetry using satellite digital twins

Reply

Same Category

Latest Reply

Announcement

Daily Top Contributors

[Other] Building and verifying end-to-end deep learning engines to detect anomalies in spacecraft telemetry using satellite digital twins Copy

Reply

Same Category

Latest Reply

Announcement

Daily Top Contributors

[Other] Building and verifying end-to-end deep learning engines to detect anomalies in spacecraft telemetry using satellite digital twins