Scopus Indexed Publications

Paper Details


Title
Mango Species Detection from Raw Leaves Using Image Processing System
Author
Most. Hasna Hena, Ahmed Al Marouf, Md. Helal Sheikh, Md. Shamim Reza,
Email
hena.cse@diu.edu.bd
Abstract

Mango is the national tree of Bangladesh which is one of the most popular fruits here during the hot summer enriching the highest quality of nutrition. Various species of mango cover the fruit market making the summer festivities. In recent times, different species of mango are also being exported to different countries of the world. So more and more people are entering into the commercial mango cultivation nowadays as new farmers. It is necessary for them to know which mango species they are cultivating and what is the market demand of that species. It is hard for the new farmers to find out the species just by asking and trusting the sapling seller. So, we plan to establish a system that can accurately ensure the species of the mango sapling. This research used convolutional neural network (CNN) and deep learning for training the dataset. This method can showcase the species of the mango sapling only by observing the image of a leaf holding an accuracy of 78.65%.

Keywords
Species Mango Image processing Convolutional neural network (CNN)
Journal or Conference Name
Smart Trends in Computing and Communications: Proceedings of SmartCom 2020
Publication Year
2021
Indexing
scopus