To bee or not to bee: Investigating machine learning approaches for beehive sound recognition
This work addresses the problem of monitoring bee health through sound analysis for beekeepers and researchers, but it is incremental as it applies existing methods to a new dataset.
The paper tackled the problem of beehive sound recognition by exploring machine learning methods, resulting in the creation and release of annotated beehive recordings and experiments with support vector machines and convolutional neural networks.
In this work, we aim to explore the potential of machine learning methods to the problem of beehive sound recognition. A major contribution of this work is the creation and release of annotations for a selection of beehive recordings. By experimenting with both support vector machines and convolutional neural networks, we explore important aspects to be considered in the development of beehive sound recognition systems using machine learning approaches.