Olive Leaf Disease Identification Framework using Inception V3 Deep Learning

Abstract

Olive has great economic and health benefits. However, it is susceptible to be infected with many diseases that cause damage to the harvested crop. Aceria Oleae is a mite that feeds on the growing points in the leaves and significantly inhibits the olive tree growth. Aceria Oleae causes leaves deformation that is known as Aculus Olearius disease. Whereas peacock spot is a fungal disease caused by Castagne fungus (Venturia Oleaginea). Peacock spot causes premature falling of the leaves and may lead to serious crop losses in the case of strong defoliation. Early detection of such diseases allows the farmers to take the appropriate countermeasures. In this paper, we present a deep learning framework based on Inception V3for the identification of olive leaf diseases. The proposed framework achieves accuracy of 96.66% which outperforms the related literature.