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Utilizing Machine Learning to Combat Plant Disease

Mohit Batra, Neha Bathla

Abstract


Plant diseases are a significant source of lost income and time for the agricultural industry. Accurately diagnosing an illness requires a high level of experience and dedication. Symptoms of plant diseases, such as spots or streaks of a different colour, are sometimes visible on the leaves of infected plants. Many fungal, bacterial, and viral organisms may also cause illness in plants. The indications and symptoms of a plant disease are assessed separately. The utilization of neural networks is rapidly broadening in various domains. Recent studies have analysed the effectiveness of ML in reviewing traditional mechanisms used to diagnose plant diseases. It has been shown that deep learning is a subset of ML that may improve accuracy with the use of a CNN model for identifying plant diseases.


Keywords


Machine learning, plant disease, detection, deep learning, CNN, accuracy parameter

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References


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