Plant Disease Detection Using Machine Learning Approaches: A Survey

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Author(s): Sukanta Ghosh (School of Computer Applications, Lovely Professional University, India), Shubhanshu Arya (School of Computer Application, Lovely Professional University, India)and Amar Singh (School of Computer Application, Lovely Professional University, India)
Copyright: 2021
Pages: 9
Source title: Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease
Source Author(s)/Editor(s): Manikant Roy (Lovely Professional University, India)and Lovi Raj Gupta (Lovely Professional University, India)
DOI: 10.4018/978-1-7998-7188-0.ch009

Keywords: Knowledge Management and Library Science / Machine Learning / Medical Information Science Reference / Medical Technologies

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Abstract

Agricultural production is one of the main factors affecting a country's domestic market situation. Many problems are the reasons for estimating crop yields, which vary in different parts of the world. Overuse of chemical fertilizers, uneven distribution of rainfall, and uneven soil fertility lead to plant diseases. This forces us to focus on effective methods for detecting plant diseases. It is important to find an effective plant disease detection technique. Plants need to be monitored from the beginning of their life cycle to avoid such diseases. Observation is a kind of visual observation, which is time-consuming, costly, and requires a lot of experience. For speeding up this process, it is necessary to automate the disease detection system. A lot of researchers have developed plant leaf detection systems based on various technologies. In this chapter, the authors discuss the potential of methods for detecting plant leaf diseases. It includes various steps such as image acquisition, image segmentation, feature extraction, and classification.

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Plant Disease Detection Using Machine Learning Approaches: A Survey

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