Plant Disease Detection using Inception V3 model and Particle Swarm Optimization

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Arivuk karasan. R, Dr. Raguraman. D


The post recognition of diseases in fruits and vegetables by farmers in India is a contributing factor in the country's declining crop yield. Farmers everywhere are suffering significant economic setbacks. The majority of the agricultural loss can be attributed to diseases that affect both plants and fruits. Farmers can boost their output by increasing their awareness of the nutritional quality of the fruits and vegetables they grow. Because of this, we are motivated to create and develop a technology that will assist farmers in detecting diseases in their crops at an early stage. The proposed research utilizes Inception V3 model which is accomplished with the help of convolutional neural networks. The performance of the Inception V3 model is enhanced by tuning its hyperparameters using Particle Swarm Optimization (PSO). The accuracy of the proposed model using Inception V3 and PSO algorithm is 0.987.


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