Research library

BeeNet: An End-To-End Deep Network For Bee Surveillance

Abstract Computer vision-based image classification plays a vital role in developing surveillance tools for measuring the biological behavior Computer classification plays a vital in developing surveillance tools for measuring the biological behavior of bees andvision-based their diseaseimage detection. Native bees often facerole numerous environmental threats, ranging from invasive bees to numerous of bees and their disease detection. Nativethe bees often face numerous environmental threats, ranging from invasive numerous parasitic diseases, which affect not only existing ecosystem but also the booming honey and wax industries.bees to Numerous MLparasitic diseases, models which affect notpotential only the in existing ecosystem but the booming and wax industries. MLbased, pre-trained showed bee classification and also monitoring tasks, honey but heavily curated data-setNumerous and closed-set based, pre-trained models showed potential in bee classification and monitoring tasks, but heavily curated data-set and closed-set models hinder their applicability in-field monitoring tasks. In this paper, we proposed a deep learning model to obtain improved modelsofhinder applicabilityofin-field.