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dc.contributor.authorSánchez San Blas, Héctor
dc.contributor.authorCarmona Balea, Antía
dc.contributor.authorSales, A.
dc.contributor.authorAugusto Silva, Luís
dc.contributor.authorVillarrubia González, Gabriel
dc.date2023-12
dc.date.accessioned2023-03-09T16:11:46Z
dc.date.available2023-03-09T16:11:46Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/14315
dc.description.abstractSpain is the second country in Europe with the most swimming pools. However, the legal literature estimates that 20% of swimming pools are not declared or irregular.The administration has a corps of people who manually analyze satellite or drone images to detect illegal or irregular structures. This method is costly in terms of effort and time, and it is also a method based on the subjectivity of the person carrying it out. This proposal aims to design a platform that allows the automatic detection of irregular pools. Using geographic information tools (GIS) based on orthophotography, combined with advanced machine learning techniques for object detection, allows this work. Furthermore, using a multi-agent architecture allows the system to be modular, with the possibility of the different parts of the system working together, balancing the workload. The proposed system has been validated by testing it in different towns in Spain. The system has shown promisin results in performing this task, with an F1-Score of 97.1%.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 8, nº 4
dc.relation.urihttps://www.ijimai.org/journal/bibcite/reference/3240es_ES
dc.rightsopenAccesses_ES
dc.subjectdeep learninges_ES
dc.subjectgeographic information systemes_ES
dc.subjectpool aerial recognitiones_ES
dc.subjectIJIMAIes_ES
dc.titleA Platform for Swimming Pool Detection and Legal Verification Using a Multi-Agent System and Remote Image Sensinges_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttps://doi.org/10.9781/ijimai.2023.01.002


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