Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/56499
Título: Secure UAV-based system to detect small boats using neural networks
Autores/as: Lodeiro-Santiago, Moisés
Caballero-Gil, Pino
Aguasca Colomo, Ricardo 
Caballero-Gil, Cándido
Clasificación UNESCO: 33 Ciencias tecnológicas
Fecha de publicación: 2019
Publicación seriada: Complexity 
Resumen: This work presents a system to detect small boats (pateras) to help tackle the problem of this type of perilous immigration. The proposal makes extensive use of emerging technologies like Unmanned Aerial Vehicles (UAV) combined with a top-performing algorithm from the field of artificial intelligence known as Deep Learning through Convolutional Neural Networks. The use of this algorithm improves current detection systems based on image processing through the application of filters thanks to the fact that the network learns to distinguish the aforementioned objects through patterns without depending on where they are located. The main result of the proposal has been a classifier that works in real time, allowing the detection of pateras and people (who may need to be rescued), kilometres away from the coast. This could be very useful for Search and Rescue teams in order to plan a rescue before an emergency occurs. Given the high sensitivity of the managed information, the proposed system includes cryptographic protocols to protect the security of communications.
URI: http://hdl.handle.net/10553/56499
ISSN: 1076-2787
DOI: 10.1155/2019/7206096
Fuente: Complexity [ISSN 1076-2787], v. 2019, article ID 7206096
Colección:Artículos
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