Abstract
Yield infections are a significant danger to food security, but its recognizable proof is troublesome because of
absence of foundation. This paper presents a survey of different image processing and deep learning
techniques used in the identification of plant disease based on images of disease infected plants. Distinguishing
and recognizing infection from the plants pictures is one of the fascinating examination territories in PC and
agribusiness field. The performance of cnn is the powerful tool to diagnose and predict the infections. The
principal objective of the undertaking is to assist farmers with recognizing the illness and to forestall the plant
in early stage. Plant sickness is the acknowledgement model, in a view of leaf picture arrangement, created
utilizing convolutional neural networks (CNN).The created model perceives 7 distinct sorts of plant illness. The
prepared model accomplishes a 99.15%of accuracy.
Keywords: Deep learning, predict, image processing, convolutional neural networks.
Modules
Algorithms
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL