Identifying Plant Disease By Using Convolution Neural Network

Authors

  • Dr.Kedri Janardhana, Dr.H.Kanagasabapathy, Mrs.M.Sangeetha

Abstract

The identification of the plant disease is crucial to obtain a good crop yield along with a good quantity of agricultural products. Detection of plant illness includes the research work of many farm-related factors such as organic farming, constant plant monitoring, and recognition of all diseases. In farms that contain entirely different crops, plant diseases cannot be tracked manually. This requires an enormous amount of work, plant disease expertise, and also a substantial amount of time. The image processing along with k-means clustering and convoluted neural networking algorithms could be used for the accurate prediction of the disease. The detection of the disease includes methods including image segregation, pre-processing data, fragmentation of the image, detection, and recognition of characteristics. This paper also examines the binding segmentation and retrieval functions of two different plant diseases.

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Published

2021-03-23 — Updated on 2021-06-07

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How to Cite

Dr.Kedri Janardhana, Dr.H.Kanagasabapathy, Mrs.M.Sangeetha. (2021). Identifying Plant Disease By Using Convolution Neural Network. International Journal of Modern Agriculture, 10(1), 1047 - 1056. Retrieved from https://modern-journals.com/index.php/ijma/article/view/713 (Original work published March 23, 2021)

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Articles