A research team has investigated low-cost depth imaging sensors with the objective of automating plant pathology tests. The team achieved 97% accuracy in distinguishing between resistant and susceptible plants based on cotyledon loss. This method operates 30 times faster than human annotation and is robust across various environments and plant densities.
Low-cost depth imaging sensors achieve 97% accuracy in rapid plant disease detection
