Deep Learning-Based Pest Surveillance System for Sericulture

Abstract

Every year sericulture farmers lose a sizeable amount of revenue because of pest attacks on silkworms. In 2011 the annual production of silk is fall by about 50% because of pest attacks [1]. To prevent these losses constant monitoring of the environment is required. But this constant surveillance can’t be achievable by manual labour force but it can be achievable by using deep learning techniques. This article presents a deep learning system that is trained and tested for detecting invasive species which can cause harm to silkworms such as Oecophylla smargdina, Vespa orientalis, Sycanus collaris, Hierodulla bipapilla, Canthecona furcellata, Blepharipa zebina and Apanteles glomeratus.