  Precision agriculture aims to use technological tools for the agro-food
sector to increase productivity, cut labor costs, and reduce the use of
resources. This work takes inspiration from bees vision to design a remote
sensing system tailored to incorporate UV-reflectance into a flower detector.
We demonstrate how this approach can provide feature-rich images for deep
learning strawberry flower detection and we apply it to a scalable, yet cost
effective aerial monitoring robotic system in the field. We also compare the
performance of our UV-G-B image detector with a similar work that utilizes RGB
images.
