Detecting Fruit Diseases Using Deep Learning and Image Analysis

The implementation of several agriculture-related issues was made simple by advancements in computer vision technology. The detection of fruit diseases is one such issue. Using deep learning techniques, a lot of study has been done on many fruits, including apples, mangos, kiwis, passion fruit, and others. The most significant contributions made by this field in recent years are outlined in this review paper. In this review, we have performed a technical analysis of deep learning methods for predicting fruit illnesses. Along with the deep learning models utilized, the study also compares various picture acquisition, image pre-processing, and segmentation methods. The study discovered that the most accurate deep learning model can vary based on the system's computing capacity and the data used. In the article directions for future research have also been covered.