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Defèr, Adrian: Classification of Honeybee Larval Stages Using CNNs Applied to Image Data

Master of Science (M.Sc.)

The decline of honey bees (Apis mellifera), due to various threats, like the ongoing global climate change or pesticides, endangers wild plant diversity, ecosystem stability and crop production. The EU funded project Hiveopolis wants to address this problem with technology. A newly developed intelligent bee colony system equipped with sensors, actuators, and robots will be used to optimally manage and guide the bee colony through nowadays challenges. Part of the research within the Hiveopolis project deals with automated methods for monitoring the brood nest on a honeycomb. Which is useful for assessing the colony strength. This thesis leverages high resolution image data of a honey bee colony, recorded with the hive observation setup, from the BeesBook project at the Biorobotic Lab, whose team also contributes to Hiveopolis, at the Freie Universität Berlin, in order to investigate how well it is possible to predict honey bee brood age with high resolution image data. (More)