A Deep Convolutional Neural Network to Detect the Existence of Geospatial Elements in High-Resolution Aerial Imagery

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