IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Image Classification of Crop Diseases and Pests Based on Deep Learning and Fuzzy System

Image Classification of Crop Diseases and Pests Based on Deep Learning and Fuzzy System
View Sample PDF
Author(s): Tongke Fan (Xi'an International University, Xi'an, China) and Jing Xu (Xi'an International University, Xi'an, China)
Copyright: 2020
Volume: 16
Issue: 2
Pages: 14
Source title: International Journal of Data Warehousing and Mining (IJDWM)
Editor(s)-in-Chief: David Taniar (Monash University, Australia)
DOI: 10.4018/IJDWM.2020040103

Purchase

View Image Classification of Crop Diseases and Pests Based on Deep Learning and Fuzzy System on the publisher's website for pricing and purchasing information.

Abstract

The automatic classification of crop disease images has important value. The classification algorithm based on manual feature extraction has some problems, such as the need for professional knowledge, is time-consuming and laborious, and has difficulty extracting high-quality features. In this article, the theory of the fuzzy system is discussed. The theory of the fuzzy system is applied to the pretreatment of blurred images. A local blurred image deblurring method based on depth learning is proposed. By training convolutional neural network models with different structures, the image of diseases and insect pests is segmented using normalized segmentation algorithms based on spectral graph theory, and the segmentation knot of leaf diseases is obtained. Finally, the optimal network structure is obtained by comparing the segmentation results with the traditional machine learning algorithm. Experiments show that the segmentation results of pests and diseases obtained by this algorithm have better robustness, generalization, and higher accuracy.

Related Content

Fatma Abdelhedi, Amal Ait Brahim, Gilles Zurfluh. © 2021. 14 pages.
Sami Belkacem, Kamel Boukhalfa. © 2021. 24 pages.
Abdelilah Balamane. © 2021. 18 pages.
I.Jeena Jacob, Betty Paulraj, P. Ebby Darney, Hoang Viet Long, Tran Manh Tuan, Harold Robinson Yesudhas, Vimal Shanmuganathan, Golden Julie Eanoch. © 2021. 17 pages.
Neha Gupta, Sakshi Jolly. © 2021. 18 pages.
Christie I. Ezeife, Vignesh Aravindan, Ritu Chaturvedi. © 2020. 21 pages.
Diego Vilela Monteiro, Rafael Duarte Coelho dos Santos, Karine Reis Ferreira. © 2020. 17 pages.
Body Bottom