An Analytical Review on Plant Leaf Disease Classification in Agriculture Area

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Richa Gupta

Abstract

In this procedure, we suggest that plant disease detection systems use imaging technology to automatically recognise the signs of a plant's ailments on its leaves and stem, assisting in the cultivation of healthy plants in a farm. These devices keep an eye on the plant's leaves and stem, and any alteration seen in its distinguishing characteristics will be automatically detected and also reported to the user. The disease detection techniques that are currently used in plants are evaluated in this work. Plant disease research focuses on a specific plant's visually discernible patterns. In order to successfully cultivate crops, it is determined that identifying plants, leaves, and stems as well as determining the presence of pests, illnesses, or their proportion are all extremely important. The method that many farmers use to find and identify plant diseases is simple observation with the unaided eye. On vast farms, it is less practical and necessitates constant observation. Additionally, non-native illnesses are unknown to the farmers. The primary goals of this research are to pinpoint the area that is afflicted, identify the disease that is present, and enhance classification performance by increasing segmentation accuracy.

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How to Cite
Gupta , R. . (2019). An Analytical Review on Plant Leaf Disease Classification in Agriculture Area. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 10(2), 954–960. https://doi.org/10.17762/turcomat.v10i2.13575
Section
Research Articles