Attention: The autoQC service is now in beta mode. We are happy that you try out the service and give us feedback or report on probable bugs.
autoQC is a tool that inlcudes classical and machine learning algorithms to support the quality control of arctic ocean temperature and salinity profile measurements. It has been developed in the M-VRE project (https://mosaic-vre.org, funded by BMBF) and got financial support by the "DataHub Earth and Environment of the Helmholtz Association" initiative. autoQC has been trained with the UDASH dataset and is based on works of the SalaciaML project (https://salacia-ml.awi.de/), which was published in Frontiers of Marine Sciences at SalaciaML. autoQC is developed at the Alfred Wegener Institute (AWI) in Bremerhaven, Germany.
Former team members:
Dr. Mohamed Chouai
Felix Reimers
Dr. Serdar Demirel
Dr. Mohamed Chouai
Felix Reimers
Dr. Serdar Demirel
If you use autoQC, please cite: https://mvre.autoqc.cloud.awi.de
Download and try with our Test data !
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UDASH arctic temperature profile with spike error.
