Professional paper
https://doi.org/10.31784/zvr.10.1.21
DEVELOPMENT OF A MOBILE APPLICATION FOR FLAG IDENTIFICATION BASED ON ARTIFICIAL NEURAL NETWORKS
Ivan Zatezalo
orcid.org/0000-0001-9245-2255
; Faculty of Humanities and Social Sciences, University of Zagreb, Zagreb, Croatia
Ivan Dunđer
; Faculty of Humanities and Social Sciences, University of Zagreb, Zagreb, Croatia
Abstract
Machine learning and more specifically its subfield known as deep learning have been driving new disruptive technologies and recent accomplishments in various industries. This paper applies to some extent the same technology to develop a mobile application for educational purposes, that allows one to identify unknown flags with the help of artificial intelligence. For the application to be functional and effective, a custom dataset had to be created and processed in various ways in order to provide a collection of data that resembles data from the real world. The collection would then be used as the input data for constructing the model, which is developed within the framework TensorFlow. Once the
model was developed, it was implemented as part of a mobile application programmed with Flutter. The functionality of the mobile application and the model’s accuracy are then put to the test against over a hundred of new images the model has not seen previously or been trained on. The result of this evaluation could be considered an estimate of the readiness and usability of the application in a real-world scenario.
Keywords
convolutional neural networks; mobile application; TensorFlow; object identification; machine learning; deep learning; artificial intelligence
Hrčak ID:
277793
URI
Publication date:
20.5.2022.
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