Tomato Leaf Disease Detection Using Deep Learning Techniques
Surampalli Ashok, G Kishore, Velpula Rajesh, S. Suchitra, S. Sophia, B. Pavithra
Abstract
Early Detection of Plant Leaf Detection is a major necessity in a growing agricultural economy like India. Not only as an agricultural economy but also with a large amount of population to feed, it is necessary that leaf diseases in plants are detected at a very early stage and predictive mechanisms to be adopted to make them safe and avoid losses to the agri-based economy. This paper proposes to identify the Tomato Plant Leaf disease using image processing techniques based on Image segmentation, clustering, and open-source algorithms, thus all contributing to a reliable, safe, and accurate system of leaf disease with the specialization to Tomato Plants.
Topics & Concepts
Cluster analysisImage segmentationAgricultureSegmentationComputer sciencePopulationDiseaseMachine learningArtificial intelligenceAgricultural engineeringBiologyEngineeringMedicineEnvironmental healthEcologyPathologySmart Agriculture and AILeaf Properties and Growth MeasurementSpectroscopy and Chemometric Analyses