• Agliya Lydia C
• Abinaya D
• Akshaya R
• Jebha Glory P
• Kavitha M

This project automates the identification of medicinal plants and leaves using deep learning, specifically DenseNet architecture in Python. Implemented as a web application with Flask, it allows users to upload images for accurate classification. The system uses two datasets for plants and leaves, each pre-processed and trained separately. The trained models are deployed for real-time predictions, providing high accuracy and additional medicinal information. This approach reduces dependency on expert knowledge and promotes access to valuable medicinal information, supporting traditional medicine, pharmacology, and conservation efforts.

Medicinal plant identification, image processing, deep learning, convolutional neural networks, plant species classification.

"GREEN REMEDY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.a917-a927, May-2025, Available :http://www.jetir.org/papers/JETIR2505100.pdf

"GREEN REMEDY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppa917-a927, May-2025, Available at : http://www.jetir.org/papers/JETIR2505100.pdf