An enhanced feature based classification model for plant diseases detection using CNN technique
Abstract
The agriculture industry is vital to maintaining global food security, prompt and precise plant disease detection is critical to crop protection and yield optimization. Conventional techniques for diagnosing diseases frequently depend on skilled professionals’ subjective and time-consuming visual assessment. Deep learning methods have become effective instruments for automating plant disease identification and diagnosis in recent years, with the promise for quick and accurate evaluation. The capacity of the suggested convolutional neural network (CNN)-based model to detect plant diseases to capture complex patterns and temporal relationships in a variety of plant datasets is critically analysed.
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DOI: https://doi.org/10.32629/jai.v7i5.1521
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