Використання нейронних мереж у розпізнаванні хвороб рослин
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Date
2021-12-10
Authors
Афонін, Андрій
Кундік, Кирило
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Abstract
У статті описано розроблену модель нейронної мережі, що дає змогу розпізнавати хвороби рослин за зображенням їхнього листя. Модель має високу точність і швидкий час передбачення. Детально висвітлено проведене дослідження сучасних архітектур моделей глибинного навчання з акцентом на досягнення найвищої точності та найменшої помилки при вирішенні задачі класифікації зображень. Продемонстровано ефективність запропонованих рішень на прикладі створення автоматизованої системи розпізнавання хвороб сільськогосподарських рослин.
Machine learning technologies have developed rapidly in recent years, and people are now able to use them in various spheres of life, making their lives easier and better. The agro-industry is not lagging behind, and every year more and more problems in this area are solved with the help of machine learning algorithms. However, among the problems that have not yet been solved is the problem of identifying diseases of agricultural plants. According to the UN research, about 40% of the world’s harvest dies each year from various diseases, most of which could be avoided through timely intervention and treatment. To solve this problem, we offer an easy, accessible service for everyone, which will allow one to predict by the image of the plant leaves whether it is sick or healthy, or whether it needs any help or intrusion. This service will be indispensable for small farms engaged in growing crops. Thus, it will allow employees of such enterprises to immediately detect diseases and receive recommendations for the care of plants important to them. Therefore, it was decided to develop a neural network architecture that will solve this problem: the prediction of a plant disease by the image of its leaves. This neural network model is lightweight, does not take much time to learn, and has high accuracy on our dataset. It was also investigated which popular architectures (e.g. XceptionNet, DenseNet, etc.) of deep neural networks can have great accuracy in solving this problem. To realize the possibility of using the model by end users, i.e. farmers, it was decided to develop a special web service in the form of a telegram bot. With this bot, anyone can upload images of the leaves of agricultural plants and check whether this plant is healthy or free of any diseases. This bot is also trained to give appropriate advice to gardeners on the treatment of diseases or the proper cultivation of healthy plants. This solution fully solves the problem and has every chance to become an indispensable helper in preserving the world harvest.
Machine learning technologies have developed rapidly in recent years, and people are now able to use them in various spheres of life, making their lives easier and better. The agro-industry is not lagging behind, and every year more and more problems in this area are solved with the help of machine learning algorithms. However, among the problems that have not yet been solved is the problem of identifying diseases of agricultural plants. According to the UN research, about 40% of the world’s harvest dies each year from various diseases, most of which could be avoided through timely intervention and treatment. To solve this problem, we offer an easy, accessible service for everyone, which will allow one to predict by the image of the plant leaves whether it is sick or healthy, or whether it needs any help or intrusion. This service will be indispensable for small farms engaged in growing crops. Thus, it will allow employees of such enterprises to immediately detect diseases and receive recommendations for the care of plants important to them. Therefore, it was decided to develop a neural network architecture that will solve this problem: the prediction of a plant disease by the image of its leaves. This neural network model is lightweight, does not take much time to learn, and has high accuracy on our dataset. It was also investigated which popular architectures (e.g. XceptionNet, DenseNet, etc.) of deep neural networks can have great accuracy in solving this problem. To realize the possibility of using the model by end users, i.e. farmers, it was decided to develop a special web service in the form of a telegram bot. With this bot, anyone can upload images of the leaves of agricultural plants and check whether this plant is healthy or free of any diseases. This bot is also trained to give appropriate advice to gardeners on the treatment of diseases or the proper cultivation of healthy plants. This solution fully solves the problem and has every chance to become an indispensable helper in preserving the world harvest.
Description
Keywords
машинне навчання, класифікація зображень, комп’ютерний зір, глибинне навчання, Tensorflow, хвороби сільськогосподарських рослин, стаття, machine learning, image classification, computer vision, deep learning, Tensorflow, agricultural plant diseases, article
Citation
Афонін А.О. Використання нейронних мереж у розпізнаванні хвороб рослин / Афонін А. О., Кундік К. В. // Наукові записки НаУКМА. Комп'ютерні науки. - 2021. - Т. 4. - С. 23-28. - https://doi.org/10.18523/2617-3808.2021.4.23-28