Detecting the Infectious Area Along with Disease Using Deep Learning in Tomato Plant Leaves
Piyush Juyal, Sachin Sharma
Abstract
Plant diseases adversely affect the production of crops and, on certain occasions, the production itself, which places the farmer in a precarious position. This reduced growth is impacting farmers and triggering food shortages that are harming our society's lower classes. We can help farmers diagnose the disease with deep learning and correctly remedy their crops. This timely intervention would help to improve the survival rate of crops, and the yield will be higher and healthier. We propose a technique in which we use the R-CNN mask to correctly identify and accurately mask the disease-infected region. Fast identification will help farmers respond quickly against these disorders.
Topics & Concepts
Economic shortageDiseaseDeep learningProduction (economics)Yield (engineering)Plant diseaseIdentification (biology)Infectious disease (medical specialty)BiotechnologyComputer scienceArtificial intelligenceAgroforestryMedicineBiologyEconomicsPathologyBotanyMacroeconomicsLinguisticsMetallurgyPhilosophyMaterials scienceGovernment (linguistics)Smart Agriculture and AISpectroscopy and Chemometric AnalysesLeaf Properties and Growth Measurement