Machine Learning and Deep Learning for the Detection and Classification of Hemp Disease

Surveer Thakur

Abstract


Hemp is a useful plant for both industrial and medical purposes. The plant is simple to cultivate, requires little care, and may be used in any region. Hemp infections, like those that afflict other plants, may have a major impact on plant development and, as a result, hemp production suffers economically. Researchers have begun to use data-driven machine learning techniques in smart agriculture and farming due to significant advancements in artificial intelligence and machine learning technologies. The identification and categorization of plant diseases is an example of smart agriculture in action. This study proposes one SVM-based machine learning model and three deep learning algorithms for detecting and classifying hemp illness.


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