Identification of medicinal plant using hybrid transfer learning technique

• Published in: Indonesian Journal of Electrical Engineering and Computer Science Vol. 31; no. 3; p. 1605
• Main Authors: Ghosh, Sukanta, Singh, Amar, Kumar, Shakti
• Format: Journal Article
• Language: English
• Published: 01.09.2023
• ISSN: 2502-4752; 2502-4760
• DOI: 10.11591/ijeecs.v31.i3.pp1605-1615

Ayurveda is one of the oldest holistic treatment systems in the world. Finding an accurate and correct plant is the key to the working of Ayurvedic treatment. Identification of medicinal plants is a tedious job due to the look-alike feature and availability issue of medicinal plants with other plants. This paper emphases on the ideal identification and classification of plants of medicinal use using deep learning approaches. Previously researchers have used traditional machine learning techniques to identify medicinal plants, which lead to mixed results. Such results are good but not enough as the identification of medicinal plants may lead to a worsening situation for patients. This research is conducted to get results closer to an ayurvedic expert. The dataset used for this research has been taken from Mendeley Data. The dataset comprises 30 different species of medicinal plants. Hybrid transfer learning has been applied to this dataset. The model has generated a test accuracy of 95.25% which is better than the other popular transfer learning techniques.