A Systematic Analysis on Leaf Disease Detection and Classification Using Machine Learning

One of the most crucial areas of precision agriculture research is the identification of plant diseases using images of their leaves. Since most plant diseases have a variety of outwardly visible symptoms, learning models should be highly observant to identify the telltale indicators of any disease. Currently, several kinds of machine learning techniques are employed to identify plant diseases. This study presents a Survey on Leaf Disease Classification and Detection Techniques offers a thorough investigation into the application of various algorithmic approaches. Hence, this extensive review highlights the nuances and capabilities of machine learning and deep learning models, particularly in their application to diverse various plants. This comprehensive overview showcasing the evolving landscape of plant pathology research driven by advanced computational techniques.

Authors

Publication Details

Journal
Journal of Emerging Technologies and Innovative Research
Published
2025-01-01
DOI
https://doi.org/10.56975/jetir.v12i5.563292
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

A Systematic Analysis on Leaf Disease Detection and Classification Using Machine Learning

K. Usha Rani, Vijaya Battini
Journal of Emerging Technologies and Innovative Research
Smart Agriculture and AI
article

A Systematic Analysis on Leaf Disease Detection and Classification Using Machine Learning

K. Usha Rani, Vijaya Battini
article en

Abstract

One of the most crucial areas of precision agriculture research is the identification of plant diseases using images of their leaves. Since most plant diseases have a variety of outwardly visible symptoms, learning models should be highly observant to identify the telltale indicators of any disease. Currently, several kinds of machine learning techniques are employed to identify plant diseases. This study presents a Survey on Leaf Disease Classification and Detection Techniques offers a thorough investigation into the application of various algorithmic approaches. Hence, this extensive review highlights the nuances and capabilities of machine learning and deep learning models, particularly in their application to diverse various plants. This comprehensive overview showcasing the evolving landscape of plant pathology research driven by advanced computational techniques.

Journal of Emerging Technologies and Innovative ResearchVol. 12(5)
Openalex Percentile: Top 91%
Smart Agriculture and AI
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