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
- K. Usha Rani (ORCID: https://orcid.org/0009-0006-7000-026X)
- Vijaya Battini
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