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Harnessing deep learning for medicinal plant research: a comprehensive study

Ananda, Vidya HullekereRao, Narasimha Murthy Madiwala SathyanarayanaKrishnamurthy, Thara Dharmapura
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 Februari 2025
DOI10.11591/ijece.v15i1.pp908-920

Abstrak

In today’s world, people are more prone to diseases due to food adulteration and pollution in the environment, and people have found a way of using herbal medicine as an alternative to allopathic medicine, especially since coronavirus disease 2019 (COVID-19). Medicinal plants are the source of herbal medicines that increase the immunity of humans. Medicinal plants are used in many applications, like pharmaceuticals, cosmetics, and drugs. Medicinal plants are of great importance, and hence this work presents a review of the medicinal plants grown in Karnataka State, India. The work also highlights species identification and disease detection of medicinal plants employing machine learning and deep learning approaches. The paper provides information about datasets available for various medicinal plant leaf images. The deep learning models used for species identification and disease detection in medicinal plants have been discussed along with the results.

Kata Kunci

Computer ScienceArtificial IntelligenceMachine LearningDeep LearningDeep learningDisease detectionMachine learningMedicinal plantsSpecies identification

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Harnessing deep learning for medicinal plant research: a comprehensive study | International Journal of Electrical and Computer Engineering (IJECE) | Publiora