Affiliation:
1. Inner Mongolia Agricultural University, Hohhot 010018, China
2. Inner Mongolia Autonomous Region Key Laboratory of Big Data Research and Application of Agriculture and Animal Husbandry, Hohhot 010018, China
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.
Funder
Natural Science Foundation of Inner Mongolia Autonomous Region of China
Research Program of science and technology at Universities of Inner Mongolia Autonomous Region of China
National Natural Science Foundation of China
Inner Mongolia Agricultural University High-level Talent Research Start-up Project
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
15 articles.
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