A deep transfer learning based approach to detect medicinal plants

Abstract

The identification of medicinal plants plays a crucial role in healthcare, particularly in countries like Bangladesh, known for a rich diversity of medicinal flora. However, the accurate recognition of these plants remains a challenge for many. To address this, a novel mobile application is proposed, leveraging the Android platform for the user interface and employing machine learning techniques for image processing and plant identification. This application aims to assist individuals in accurately identifying various medicinal plants, thereby contributing to widespread accessibility of valuable botanical knowledge. The integration of machine learning algorithms will enable users to capture plant images, which will be processed and matched against an extensive database, providing users with real-time identification results. This initiative holds the potential to benefit a broad spectrum of users, including healthcare professionals, researchers, and the general public, thereby fostering a deeper understanding and utilization of the diverse array of medicinal plants indigenous to Bangladesh. This paper proposes a machine learning technique to detect Alzheimer's disease in Bangladesh. The proposed system comprises of three components. First, a set of demographics, clinical and laboratory data are collected from web. This data is then pre-processed using feature selection and normalization techniques.