Scopus Indexed Publications

Paper Details


Title
MediNET: A Deep Learning Approach to Recognize Bangladeshi Ordinary Medicinal Plants Using CNN
Author
Md. Rafiuzzaman Bhuiyan, Md. Abdullahil-Oaphy, Md. Sanzidul Islam, Rifa Shanzida Khanam,
Email
rafiuzzaman15-9655@diu.edu.bd
Abstract

Medicine is the only thing by which we use where we feel bad condition of our body’s physical and mental illness. Most of medicines are made of specific plants from our nature. These plants are also known as a medicinal plant. All the traditional Bangladeshi medical systems, namely Ayurveda, Unani, Homeopathy, prominently use medicinal plants. So, it is important to classify the right plant for medical preparation. The ability to identify these plants automatically is needed in recent days. For this, we proposed a renowned algorithm called convolutional neural network for recognizing the plants from leaf image. Our algorithm got 84.58% accuracy. We developed this. We believe that in the future the individuals who do not distinguish medicinal plants will recognize using this methodology.

Keywords
Medicinal plant Plant recognition Convolutional neural network
Journal or Conference Name
Soft Computing Techniques and Applications, Advances in Intelligent Systems and Computing
Publication Year
2021
Indexing
scopus