Leaf Disease Identification Using Model Hybrid Based on Convolutional Neuronal Networks and K-Means Algorithms

Joel Bejar Mallma, Ciro Rodriguez, Yuri Pomachagua, Carlos Navarro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Plant leaf diseases usually affect agriculture a lot, which is one of the important sources of income for people, so diseases must be detected and recognized quickly and effectively. The research aims to identify these diseases automatically using a model based on deep learning known as convolutional neural networks and the K-means algorithm. The methodology applied for the detection, three previously trained networks, VGG16, VGG19, and ResNet50, were used for the extraction of characteristics, the principal component analysis algorithm was also used to reduce dimensionality, and finally, the K-means algorithm classification. The training of the models was carried out with the use of a Kaggle open database of 7771 images which contain 38 types of diseases and healthy leaves. VGG16, VGG19, and ResNet50 were trained where the accuracy of 97.43%, 98.35%, and 98.38% was obtained. The precision obtained with the VGG16 hybrid model and the K-means algorithm was 96.26%. Therefore, the hybrid model is effective for the identification of plant diseases.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 13th International Conference on Computational Intelligence and Communication Networks, CICN 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages161-166
Number of pages6
ISBN (Electronic)9781728176956
DOIs
StatePublished - 22 Sep 2021
Event13th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2021 - Lima, Peru
Duration: 22 Sep 202123 Sep 2021

Publication series

NameProceedings - 2021 IEEE 13th International Conference on Computational Intelligence and Communication Networks, CICN 2021

Conference

Conference13th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2021
Country/TerritoryPeru
CityLima
Period22/09/2123/09/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

  • CN
  • K-means algorithm
  • VGG16
  • leaf disease
  • machine learning

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