Year: 2025
Type: article
Abstract: Planet leaf identification for medicinal usage is a slow and human error-prone task based on expert manual identification. Classifying plant leaves according to their type and medicinal use is challenging based on current research that assigns a new approach through DL& (AI). The suggested system employs a (CNN) in filtering the visual characteristics of the planet leaves and (NLP) techniques in extracting information from the history of the leaf and medicine applied in disease treatment. The suggested system achieved an accuracy level of 95% in classifying the type of leaves and medical use. The outcome justifies the suggested system's effectiveness, accuracy, and potential in redefining plant leaf identification and classification for medicinal usage. The current paper expounds on the suggested system, methodology, result analysis, and conclusion.
Author: K. Satvika
Institution: Jawaharlal Nehru Technological University, Hyderabad
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409292608