Plant Disease Identification Using Deep Learning

This paper presents an AI-based plant disease identification system that utilizes deep learning algorithms such as ResNet50, MobileNet, and Inception V3. The proposed system is divided into two phases: the training phase and the testing phase. In the training phase, the collected dataset undergoes preprocessing, data cleaning, feature extraction where data augmentation is also applied to prevent the neural network from learning irrelevant patterns, thereby boosting overall performance. Once the dataset is optimized, it is fed to the deep learning algorithm to create a model that can predict the disease of an infected plant. Finally, during the testing phase the model shall be given an input image where distinct unique patterns will be extracted and the prediction would be displayed