TITLE
APPLICATION OF NEURAL NETWORKS IN ANDROID APPLICATIONS FOR OBJECT RECOGNITION IN REAL TIME
AUTHOR(S)
Zeljko Jovanovic, Filip Petrovic, Mihailo Knezevic
ABSTRACT
This paper describes how neural networks can be used in Android applications. Specifically, an educational application for language learning based on a neural network model was developed. Several neural network models were trained for object detection as part of the practical part. With the help of these models, an
application that detects objects in real-time and translates them into the desired language was created. Several topics were explored in this paper, such as neural networks, artificial intelligence, android platform, TensorFlow and TensorFlow Lite libraries and how they work, and the concept of detection, i.e., object
recognition. In addition to the theoretical part, which is necessary to understand how neural networks work and the Android platform, each step of the practical demonstration is described in detail. This includes preparing the working environment, training the data set, training the neural network, and developing the Android application.
DOI
www.doi.org/10.70456/IGXF8861
PAGES
149-154
DOWNLOAD
https://unitechsp.tugab.bg/images/2023/4-KS/s5_p78_v4.pdf
How to cite this article:
Zeljko Jovanovic, Filip Petrovic, Mihailo Knezevic, APPLICATION OF NEURAL NETWORKS IN ANDROID APPLICATIONS FOR OBJECT RECOGNITION IN REAL TIME, UNITECH – SELECTED PAPERS - 2024, 149-154