Classification of Medicinal Plants Leaves Using Deep Learning Technique: A Review

Authors

Keywords:

Medicinal plants classification, Machine learning, Plant disease, Deep learning, Leaf pattern recognition

Abstract

Pharmaceutical companies are increasingly using medicinal plants since they are less costly and have less adverse effects than current drugs. As a result, a lot of academics are very interested in studying automatic medicinal plant classification. A powerful classifier that can accurately categorize therapeutic plants in real time must be created. This article reviews the effectiveness and predictability of many machine learning and deep learning algorithms deployed in recent years to categorize plants using pictures of their leaves. This study contains image processing techniques for some classifiers that are used to recognize leaves and extract important leaf characteristics. Early plant disease identification is essential because plant diseases have an impact on the growth of their specific species. There are several Machine learning models that are used to identify and classify the signs of plant diseases, but recent advancements in Deep Learning, a subset of ML, seem to offer tremendous promise for improved accuracy. The ML and DL models used to categorize different plant leaves are thoroughly reviewed in this article.

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References

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Basic concepts of plant recognition [4]

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Published

16.12.2022

How to Cite

Chanyal, H. ., Yadav, R. K. ., & Saini, D. K. J. . (2022). Classification of Medicinal Plants Leaves Using Deep Learning Technique: A Review. International Journal of Intelligent Systems and Applications in Engineering, 10(4), 78–87. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2199

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Research Article