Application of neural networks to image recognition of wheat rust diseases

Mikhail Genaev, Skolotneva Ekaterina, Dmitry Afonnikov

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

Abstract

Rust diseases of cereals are caused by pathogenic fungi and can significantly reduce plant productivity. Many cultures are subject to them. The disease is difficult to control on a large scale, so one of the most relevant approaches is crop monitoring, which helps to identify the disease at an early stage and make efforts to prevent its spread. One of the most effective methods of control is the identification of the disease from digital images that obtained by a smartphone camera. In this paper, we present a deep learning algorithm that uses a digital image of wheat plants to determine whether they are affected by a disease and, if so, what type: leaf rust or stem rust. The algorithm based on the convolution neural network of the densenet architecture. The resulting model demonstrates high accuracy of classification: the measure of accuracy F1 on the validation sample is 0.9, the AUC averaged over 3 classes is 0.98.

Original languageEnglish
Title of host publicationProceedings - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages40-42
Number of pages3
ISBN (Electronic)9781728195971
DOIs
Publication statusPublished - Jul 2020
Event2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020 - Novosibirsk, Russian Federation
Duration: 6 Jul 202010 Jul 2020

Publication series

NameProceedings - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020

Conference

Conference2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020
CountryRussian Federation
CityNovosibirsk
Period06.07.202010.07.2020

Keywords

  • CNN
  • deep learning
  • image analysis
  • leaf rust
  • phenotyping
  • stem rust
  • wheat

OECD FOS+WOS

  • 1.02 COMPUTER AND INFORMATION SCIENCES
  • 1.06 BIOLOGICAL SCIENCES
  • 3.01 BASIC MEDICAL RESEARCH
  • 5.09 OTHER SOCIAL SCIENCES

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