Prediction and Analysis of Plant-Leaf Disease in Agricultural by using Image Processing and Machine Learning Techniques

被引：0

作者：

Babu, T. R. Ganesh ^{[1
]}

Priya, S. ^{[1
]}

Chandru, J. Gopi ^{[1
]}

Balamurugan, M. ^{[1
]}

Gopika, J. ^{[1
]}

Praveena, R. ^{[1
]}

机构：

[1] Muthayammal Engn Coll, Dept Elect & Commun Engn, Namakkal, Tamil Nadu, India

来源：

2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PERFORMANCE EVALUATION (COMPE-2021) | 2021年

关键词：

Agriculture; plant-leaf disease; image processing; fungal; Multi-layer feed-forward neural networks and machine learning;

D O I：

10.1109/ComPE53109.2021.9751855

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

India is a region for agriculture. Currently, India is the second highest manufacturer of agriculture worldwide. Throughout the meantime, a modern definition of smart agriculture has been developed, which regulates and tracks farm conditions utilizing the own operating systems. In agriculture Fungal or fungal-like species are the cause of plant diseases around 85 per cent in the world. However, viral and bacterial species cause many harmful diseases in grain and feed crops. Some microbes inflict herbal illness, too. Some vegetable conditions are categorized as "biotic" or as non-infectious diseases, which in involve air pollution injury, nutritional deficiencies or toxicities. In this study we implemented a machine learning approach like Multi-layer feed-forward neural networks and image processing techniques to predict plant leaf disease causes of agriculture field.

引用

页码：540 / 544

页数：5

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