A Lightweight Neural Network-Based Method for Identifying Early-Blight and Late-Blight Leaves of Potato

Applied Sciences(2023)

Cited 6|Views2
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Abstract
Crop pests and diseases are one of the most critical disasters that limit agricultural production. In this paper, we trained a lightweight convolutional neural network model and built a Django framework-based potato disease leaf recognition system, which can recognize three types of potato leaf images including early blight, late blight, and healthy. A lightweight, neural network-based model for the identification of early potato leaf diseases significantly reduces the number of model parameters, whereas the accuracy of Top-1 identification is over 93%. We imported the trained model into the Django framework to build a website for a potato early leaf disease identification system, thus providing technical support for the implementation of a mobile-based potato leaf disease identification and early warning system.
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Key words
convolutional neural networks,machine learning,potato disease leaf,Django framework
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