مقاله انگلیسی رایگان در مورد یادگیری ماشین برای طبقه بندی و تشخیص بیماریهای برگی گیاه – 2019 IEEE

I- Introduction

II- Classification of plant diseases

III- Classification algorithms

IV- Conclusion

References

Abstract

Plants are considered to be important as they are the source of energy supply to mankind. Plant diseases can affect the leaf any time between sowing and harvesting which leads to huge loss on the production of crop and economical value of market. Therefore, leaf disease detection plays a vital role in agricultural field. However, it requires huge manpower, more processing time and extensive knowledge about plant diseases. Hence, machine learning is applied to detect diseases in plant leaves as it analyzes the data from different aspects, and classifies it into one of the predefined set of classes. The morphological features and properties like color, intensity and dimensions of the plant leaves are taken into consideration for classification. This paper presents an overview on various types of plant diseases and different classification techniques in machine learning that are used for identifying diseases in different plant leaves.

INTRODUCTION

INDIA is a fast developing country and agriculture is the back bone for the country’s development in its early stage. However, agricultural field faces lots of hurdles including huge loss in the crop production. Plant leaf diseases are one of the important reasons for the loss in the production and plant leaf disease identification is also very difficult in agriculture field. Naked eye method is a traditional method of identifying the diseases which involves huge man power, inaccurate, time consuming and not applicable for larger fields. In addition, it is very expensive as it requires continuous monitoring by the experts. Hence, machine learning; a reliable prediction methodology is used for detecting various diseases of plant leaves caused by fungus, bacteria and virus. However, disease prediction using classification algorithms appears to be a difficult task as the accuracy varies for different input data. In this paper, several research contributions related to various plant leaf diseases detection using different classification algorithms are reviewed and compared.