A Computer Vision System for Guava Disease Detection and Recommend Curative Solution Using Deep Learning Approach

Guava disease has become a tremendous problem for the production of guava which has undeviating effect on the socioeconomic development of the farmers. This phenomenon leads to initiate an automated computer vision based guava disease detection system that may detect malicious guava and guide to early cure approaches, resulting reduction of relative economic loss. Considering the fact, in this paper we have proposed a convolutional neural network (CNN) based guava disease detection and curative suggestion providing system. We have collected the images of guava affected by anthracnose, fruit rot and fruit canker along with disease free guava from different districts of Bangladesh. In this paper, we have applied three CNN models and experimentally found that the third model has outperformed the other two with an accuracy of 95.61%. For meticulous experimentation, performance metrics like precision, recall and F1 score is evaluated and found to yield great results.