See as a Bee: UV Sensor for Aerial Strawberry Crop Monitoring
Megan Heath, Ali Imran, David St-Onge
- Year
- 2022
- Access
- Open access
Abstract
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.
Keywords
Related papers
Parallel Differentiable Reachability for Learning and Planning with Certified Neural Dynamics and Controllers
Keyi Shen, Glen Chou
2026
Artificial Intelligence enhanced smart welding islands: Foundation models revolutionizing manufacturing
Xiwei Wu, Wei Wu, Qiqi Chen +6 more
Robotics and Computer-Integrated Manufacturing · 2026
A deep reinforcement learning and a dynamic graph neural network-based scheduling agent to control a multi-task robot
Hedi Boukamcha, Anas Neumann, Monia Rekik +3 more
Robotics and Computer-Integrated Manufacturing · 2026
LLM Agent-driven Automated DFA Assessment with Fine-tuning and AAS-based RAG
Jiaxin Liu, Xiaofeng Zhou, Suyang Yu +5 more
Robotics and Computer-Integrated Manufacturing · 2026