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Deep Learning based Plant Leaf Disease Detection and Classification

S. H. Annie Silviya, B Sriman, Baby Shamini P, A. Elangovan, Monica A. R, N.V. Keerthana

20222022 4th International Conference on Inventive Research in Computing Applications (ICIRCA)16 citationsDOI

Abstract

Plant diseases can reduce the quality and quantity of agricultural products. Finding plant life - threatening infections is critical for public health and well-being. Automatic detection disease diagnosis is becoming a popular area of study. It aids in the monitoring of large crop fields and the detection of parasitic infection on the leaves. The goal of this article is to pinpoint crop damage that reduce crop losses and, as a result, increase production efficiency. Our proposed framework detects leaf diseases at an early level and identifies crop diseases based on symptoms using only a Convolutional (DL) technique. The suggested technique of the system recognizes illness using a CNN, with the maximum accuracy of our suggested method. Finally, the result is displayed in the system's Graphical User Interface Output. The experimental results show that the system performs better.

Topics & Concepts

Computer scienceCropPlant diseaseAgricultureArtificial intelligenceCrop productionAgricultural engineeringDeep learningQuality (philosophy)Machine learningAgronomyBiotechnologyEngineeringBiologyPhilosophyEcologyEpistemologySmart Agriculture and AILeaf Properties and Growth MeasurementGreenhouse Technology and Climate Control
Deep Learning based Plant Leaf Disease Detection and Classification | Litcius