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Authors: Fabricio Torrico-Pacherre ; Ian Maguiña-Mendoza and Willy Ugarte

Affiliation: Universidad Peruana de Ciencias Aplicadas (UPC), Lima, Peru

Keyword(s): VGG16, SOA, Tourism, Application, Place Recognition, Neural Network, Image Processing.

Abstract: A mobile application was developed for the recognition of places from a photo using the technique “content based photo geolocation as spatial database queries”. For this purpose, an investigation and analysis of the different existing methods that allow us to recognize images from a photo was carried out in order to select the best possible model and then improve it. Performance comparisons, comparison of number of parameters, Error: imagenet and the Brain-Score were made; once the best model was obtained, the algorithm was implemented and with the results the expected information of the place in the photo was shown. The purpose of this information is to recommend nearby places of interest. In the development stage, first, we implement an architecture with convolutional neural networks VGG16, for the recognition of places, the model was trained, after obtaining a trained model with successful results, the construction phase of the application continued. mobile in order to test the op eration of the model. Users will use the app by submitting a photo which will query the trained model, and results will be obtained in seconds, information that will provide a better experience when visiting unknown places. (More)

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Paper citation in several formats:
Torrico-Pacherre, F.; Maguiña-Mendoza, I. and Ugarte, W. (2022). Detecting Turistic Places with Convolutional Neural Networks. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-569-2; ISSN 2184-4992, SciTePress, pages 471-478. DOI: 10.5220/0010992500003179

@conference{iceis22,
author={Fabricio Torrico{-}Pacherre. and Ian Maguiña{-}Mendoza. and Willy Ugarte.},
title={Detecting Turistic Places with Convolutional Neural Networks},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2022},
pages={471-478},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010992500003179},
isbn={978-989-758-569-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Detecting Turistic Places with Convolutional Neural Networks
SN - 978-989-758-569-2
IS - 2184-4992
AU - Torrico-Pacherre, F.
AU - Maguiña-Mendoza, I.
AU - Ugarte, W.
PY - 2022
SP - 471
EP - 478
DO - 10.5220/0010992500003179
PB - SciTePress