Machine learning and computer vision are dynamically growing fields, which
have proven to be able to solve very complex tasks. They could also be used for
the monitoring of the honeybee colonies and for the inspection of their health
state, which could identify potentially dangerous states before the situation
is critical, or to better plan periodic bee colony inspections and therefore
save significant costs. In this paper, we present an overview of the
state-of-the-art computer vision and machine learning applications used for bee
monitoring. We also demonstrate the potential of those methods as an example of
an automated bee counter algorithm. The paper is aimed at veterinary and
apidology professionals and experts, who might not be familiar with machine
learning to introduce to them its possibilities, therefore each family of
applications is opened by a brief theoretical introduction and motivation
related to its base method. We hope that this paper will inspire other
scientists to use the machine learning techniques for other applications in bee
monitoring.

介绍机器学习和计算机视觉技术在蜜蜂监测中的应用，以及它们作为自动蜜蜂计数算法的潜力。这篇论文旨在向兽医和蜜蜂专业人士介绍机器学习的可能性，并希望能激励其他科学家使用机器学习技术进行蜜蜂监测的其他应用。