CNN BASED IDENTIFICATION OF PLANT DISEASES FROM LEAF  IMAGES

Mr. B. SUMAN,  SHRUTI PANDEY, CHANDANA GUDIPUDI,  SURAM BHUVANA

CNN BASED IDENTIFICATION OF PLANT DISEASES FROM LEAF IMAGES

Authors

Mr. B. SUMAN, SHRUTI PANDEY, CHANDANA GUDIPUDI, SURAM BHUVANA

Keywords:

Plant Diseases Identification, Convolutional Neural Network Model, Machine Learning, Leaf images, Deep Learning, Image Processing, Agriculture Technology, Transfer Learning, Plant Pathology, Feature Extraction

Abstract

Plant study now uses an efficient and cost-effective method for identifying plant diseases from leafimages because of the development of plant phenomics. Convolutional neural networks (CNN) are the most widelyused technology for identifying plant diseases due to their exceptional performance.

References

J. Fan, Y. Zhang, W. Wen, S. Gu, X. Lu, and X. Guo, “The future of Internet of Things in agriculture:

Plant high-throughput phenotypic platform,” J. Cleaner Prod., vol. 280, 2021, Art. no. 123651.

S. Kolhar and J. Jagtap, “Plant trait estimation and classification studies in plant phenotyping using machine vision – a review,” Inf. Process. Agriculture, 2021.

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Published

2024-02-15

How to Cite

Mr. B. SUMAN, SHRUTI PANDEY, CHANDANA GUDIPUDI, SURAM BHUVANA. (2024). CNN BASED IDENTIFICATION OF PLANT DISEASES FROM LEAF IMAGES . Journal of Computational Analysis and Applications (JoCAAA), 32(2), 378–386. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2712