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Descripción
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| Abstract: This paper tackles the problem of object recognition in high-resolution aerial imagery and addresses the application of Deep Learning techniques to solve a challenge related to detecting the existence of geospatial elements (road network) in the available cartographic support. This challenge is addressed by building a convolutional neural network (CNN) trained to detect roads in high resolution aerial orthophotos divided in tiles (256 × 256 pixels) using manually labelled data. Keywords: convolutional neural network; remote sensing; road detection | |
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Internacional
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No |
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Nombre congreso
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II Congreso en Ingeniería Geomática |
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Tipo de participación
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960 |
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Lugar del congreso
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Madrid |
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Revisores
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Si |
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ISBN o ISSN
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2504-3900 |
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DOI
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https://doi.org/10.3390/proceedings2019019017 |
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Fecha inicio congreso
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26/06/2019 |
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Fecha fin congreso
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27/06/2019 |
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Desde la página
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0 |
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Hasta la página
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0 |
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Título de las actas
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The II Geomatics Engineering Conference |