A Review of Machine Learning and Deep Learning Approaches for Tulsi Classification in Health Monitoring and Species Identification

This review explores the effectiveness of Machine Learning (ML) techniques in identifying and categorizing diseases affecting Tulsi (Ocimum sanctum) leaves. Tulsi, or holy basil, is renowned for its medicinal properties, including its ability to protect against infections and diseases of the liver, skin, kidney, and more. Its antioxidant properties make it beneficial for heart health and diabetes management. Deep Learning (DL) algorithms, such as Convolutional Neural Networks (CNNs) like InceptionV3 and ResNet, have been used to identify and categorize various species of the Tulsi plant. This technology automates disease detection and classification, enabling early diagnosis and effective treatment. The paper reviews various ML algorithms used for similar tasks and their accuracy, aiming to unlock Tulsi's potential as a potent natural remedy.