|
Descripción
|
|
|---|---|
| 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. | |
|
Internacional
|
Si |
|
Nombre congreso
|
The II Geomatics Engineering Conference |
|
Tipo de participación
|
960 |
|
Lugar del congreso
|
Madrid |
|
Revisores
|
Si |
|
ISBN o ISSN
|
2504-3900 |
|
DOI
|
10.3390/proceedings2019019017 |
|
Fecha inicio congreso
|
26/06/2019 |
|
Fecha fin congreso
|
27/06/2019 |
|
Desde la página
|
1 |
|
Hasta la página
|
3 |
|
Título de las actas
|
Proceedings, 2019, CIGeo 2019 The II Geomatics Engineering Conference |