Faster-RCNN Based Deep Learning Model for Pomegranate Diseases Detection and Classification

Abstract

India is the largest producer of pomegranates in the world which earns a high profit. However, due to atmospheric conditions such as temperature variations, climate, and heavy rains, pomegranate fruits become infected with various diseases, resulting in agricultural losses. The two most common diseases seen in the Karnataka region are bacterial blight and anthracnose, both of which cause a significant production loss. This paper has detected and classified these two diseases by extracting knowledge from custom trained models using Deep Learning. To overcome the traditional methods, Faster-RCNN helps us to do better object detection.