Automatic Large Scale Detection of Red Palm Weevil Infestation using Aerial and Street View Images
This addresses the threat to date growers, homeowners, and governments by enabling large-scale surveillance, though it appears incremental as it applies existing deep learning techniques to a new domain.
The researchers tackled the problem of early detection of Red Palm Weevil infestation in palm trees by developing a novel method using deep learning on aerial and street-level imagery, analyzing over 100,000 images to map and verify infested trees in urban areas.
The spread of the Red Palm Weevil has dramatically affected date growers, homeowners and governments, forcing them to deal with a constant threat to their palm trees. Early detection of palm tree infestation has been proven to be critical in order to allow treatment that may save trees from irreversible damage, and is most commonly performed by local physical access for individual tree monitoring. Here, we present a novel method for surveillance of Red Palm Weevil infested palm trees utilizing state-of-the-art deep learning algorithms, with aerial and street-level imagery data. To detect infested palm trees we analyzed over 100,000 aerial and street-images, mapping the location of palm trees in urban areas. Using this procedure, we discovered and verified infested palm trees at various locations.