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Automatic Detection of Grape, Potato and Strawberry Leaf Diseases Using CNN and Image Processing

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Data Engineering for Smart Systems

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 238))

Abstract

Day-by-day the cultivation of plants and albumen are increased speedily in order to fulfill the demand of human being and all the animals in this universe. Recently, the production rate of crop is abated due to different crop diseases. Agricultural scientists tried hard to finding the medication for the plant disorder. But the manual identification takes huge amount of time and less efficient. For the quick detection of plant disease different types of new technologies involvement with the cultivation sector bring as blessing. In this research work, deep learning process is used to diagnose the affliction and finding its cure through the images of transited leaf of “grape’’ and “strawberry”. In modern world, researchers can develop more accurate and efficient system for object detection and recognition using deep learning-based process. Here, we used convolutional-neural-network (CNN) algorithm to train the dataset where the accuracy rate is 93.63%. The farmer all over the world especially in Bangladesh can get the facilities form this work to the increment of production rate of grape and strawberry fruits through the reduction of disease and attack of insects.

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Tariqul Islam, M., Tusher, A.N. (2022). Automatic Detection of Grape, Potato and Strawberry Leaf Diseases Using CNN and Image Processing. In: Nanda, P., Verma, V.K., Srivastava, S., Gupta, R.K., Mazumdar, A.P. (eds) Data Engineering for Smart Systems. Lecture Notes in Networks and Systems, vol 238. Springer, Singapore. https://doi.org/10.1007/978-981-16-2641-8_20

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