Herbal Plant Identification Using Deep Learning

Md., Fouziya and Ch., Divija and K. Lakshmi, Priyanka and G., Swathi and N., Revathi (2025) Herbal Plant Identification Using Deep Learning. Journal of Data Science, 2025 (06). pp. 1-13. ISSN 2805-5160

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Abstract

From traditional medicine to today’s research in pharmacology, herbal plants are seen as very important. Yet, correctly identifying herbal species is challenging since many species share the same features and must be classified by experienced taxonomists. Technological advances such as deep learning have provided a way to automate this work with improved accuracy. The proposed system identifies herbal plants by analyzing their images using Convolution Neural Networks (CNNs), which are known for being effective in computer vision. To ensure the dataset is strong, I used thousands of clear leaf pictures from various herbal plant species that were taken in many environmental settings. Before training, the images were processed in stages by normalizing them, creating variations, and separating important objects. To find the most suitable CNN, VGG16, ResNet50, and MobileNetV2 were assessed based on their accuracy, how efficient they are, and whether they could be used on mobile phones. By using transfer learning, the model could take advantage of previously trained models on huge image collections

Item Type:	Article
Uncontrolled Keywords:	Herbal Plant Identification, Deep Learning, Convolution Neural Networks, Image Classification, Plant Recognition, Computer Vision, Medicinal Plants, Automated Identification, Leaf Image Analysis, Artificial Intelligence in Botany
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RS Pharmacy and materia medica T Technology > TK Electrical engineering. Electronics Nuclear engineering
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	20 Jun 2025 02:05
Last Modified:	20 Jun 2025 09:38
URI:	http://eprints.intimal.edu.my/id/eprint/2144

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