A novel dataset and deep learning object detection benchmark for grapevine pest surveillance.

ABSTRACT: Flavescence dorée (FD) poses a significant threat to grapevine health, with the American grapevine leafhopper, Scaphoideus titanus, serving as the primary vector. FD is responsible for yield losses and high production costs due to mandatory insecticide treatments, infected plant uprooting, and replanting. Another potential FD vector is the mosaic leafhopper, Orientus ishidae, commonly found in agroecosystems. The current monitoring approach, which involves periodic human identification of yellow sticky traps, is labor-intensive and time-consuming. Therefore, there is a compelling need to develop an automatic pest detection system leveraging recent advances in computer vision and deep learning techniques. However, progress in developing such a system has been hindered by the l

SUBMITTER: Checola G 

PROVIDER: S-EPMC11669504 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature