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The honeybee is a fascinating model animal to investigate how collectivebehavior emerges from (inter-)actions of thousands of individuals. Bees mayacquire unique memories throughout their lives. These experiences affect socialinteractions even over large time frames. Tracking and identifying all bees inthe colony over their lifetimes therefore may likely shed light on theinterplay of individual differences and colony behavior. This paper proposes asoftware pipeline based on two deep convolutional neural networks for thelocalization and decoding of custom binary markers that honeybees carry fromtheir first to the last day in their life. We show that this approachoutperforms similar systems proposed in recent literature. By opening thissoftware for the public, we hope that the resulting datasets will helpadvancing the understanding of honeybee collective intelligence.

Automatic localization and decoding of honeybee markers using deep convolutional neural networks