Application of neural networks to image recognition of wheat rust diseases

Mikhail Genaev, Skolotneva Ekaterina, Dmitry Afonnikov

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

Аннотация

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.

Язык оригиналаанглийский
Название основной публикацииProceedings - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы40-42
Число страниц3
ISBN (электронное издание)9781728195971
DOI
СостояниеОпубликовано - июл 2020
Событие2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020 - Novosibirsk, Российская Федерация
Продолжительность: 6 июл 202010 июл 2020

Серия публикаций

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

Конференция

Конференция2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020
СтранаРоссийская Федерация
ГородNovosibirsk
Период06.07.202010.07.2020

Fingerprint Подробные сведения о темах исследования «Application of neural networks to image recognition of wheat rust diseases». Вместе они формируют уникальный семантический отпечаток (fingerprint).

Цитировать