Anomaly Detection in Beehives using Deep Recurrent Autoencoders

@article{Davidson2020AnomalyDI,
  title={Anomaly Detection in Beehives using Deep Recurrent Autoencoders},
  author={Padraig Davidson and Michael Steininger and Florian Lautenschlager and Konstantin Kobs and Anna Krause and Andreas Hotho},
  journal={ArXiv},
  year={2020},
  volume={abs/2003.04576}
}
Precision beekeeping allows to monitor bees' living conditions by equipping beehives with sensors. The data recorded by these hives can be analyzed by machine learning models to learn behavioral patterns of or search for unusual events in bee colonies. One typical target is the early detection of bee swarming as apiarists want to avoid this due to economical reasons. Advanced methods should be able to detect any other unusual or abnormal behavior arising from illness of bees or from technical… 

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