Year: 2025
Type: article
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.
Authors: Vijaya Battini, K Usha Rani
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: bronze
OpenAlex ID: W4410898204