Scopus Indexed Publications

Paper Details


Title
Bangladeshi Local Fruits Detection and Calorie Calculator using CNN
Author
Md Al Mamun, Md Tanvir Siddiquee,
Email
Abstract

There are many varieties of local fruits in Bangladesh. Now some of them are moribund. The aim of this paper is to introduce these local and moribund fruits to the next generation and to build a local fruit model that can be used beneficially for future research in the field of local fruits. Though all Bangladeshi fruit names and their identities are already entered in the database, but all the information is not accessible always, and most people don’t know about them. There are a lot of local fruits in Bangladesh which contain so many calories that it’s beneficial to us, but the calorie content of the same is unknown. This problem can be solved by an automatic fruit identifier, which would make many people familiar with the fruits in a timely manner. The calories of the fruit detected can also be calculated using an Android app. The proposed app is not only calculating calories, but it’s introducing local fruits to the next generation. A method of deep convolutional neural networks (CNN) model is used to classify fruits from fruit images. To detect fruit and calculate its calorie content, this model is incorporated into the mobile app. In terms of accuracy, the model has reached about 98.03%. In the field of real-time fruit identification, this method is very useful.

Keywords
"local fruits , moribund , neural networks , calorie calculator , CNN"
Journal or Conference Name
Proceedings of the 18th INDIAcom; 2024 11th International Conference on Computing for Sustainable Global Development, INDIACom 2024
Publication Year
2024
Indexing
scopus