Autoencoders for Semi-Supervised Water Level Modeling in Sewer Pipes with Sparse Labeled Data

Ferran Plana Rius*, Mark P. Philipsen, Josep Maria Mirats Tur, Thomas B. Moeslund, Cecilio Angulo Bahón, Marc Casas


Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TidsskriftWater (Switzerland)
Udgave nummer3
StatusUdgivet - 1 feb. 2022

Bibliografisk note

Funding Information:
Acknowledgments: This research was supported by INLOC Robotics SL, Aalborg University (AAU) and Universitat Politecnica de Catalunya (UPC) under the umbrella of the danish Automated Sewer Inspection Robot (ASIR) project. We thank all members of the ASIR project for the insight and expertise provided that greatly assisted the research, especially our colleagues from AAU. We thank Mark P. Philipsen from AAU for assistance throughout the research development, and Thomas B. Moeslund from AAU for comments that greatly improved the manuscript. We would also like to show our gratitude to Josep Mirats Mirats Tur INLOC Robotics CTO for sharing their pearls of wisdom with us during the course of this research. We would also like to thank Cecilio Angulo from IDEAI-UPC for his advice and supervision during the research. Finally, thanks to Marc Casas we were able to access servers with powerful GPUs, where the experiments were conducted.

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.


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