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Semantic segmentation, especially for buildings, from the very high resolution (VHR) airborne images is an important task in urban mapping applications. Nowadays, the deep learning has significantly i...
This paper proposes a preliminary analysis of whether a schema matching approach can be applied for the comparison and possible the selection of geospatial standards. Schema matching is tested in the ...
We present a method for change detection in images using Conditional Adversarial Network approach. The original network architecture based on pix2pix is proposed and evaluated for difference map creat...
Land cover classification (LCC) is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classificati...
Building detection and footprint extraction are highly demanded for many remote sensing applications. Though most previous works have shown promising results, the automatic extraction of building foot...
The automated building detection in aerial images is a fundamental problem encountered in aerial and satellite images analysis. Recently, thanks to the advances in feature descriptions, Region-based C...
The recent success of deep convolutional neural networks (CNN) on a large number of applications can be attributed to large amounts of available training data and increasing computing power. In this p...
The idea of using artificial neural network has been proven useful for hyperspectral image classification. However, the high dimensionality of hyperspectral images usually leads to the failure of cons...
We propose a complete methodology for the fine registration and referencing of kilo-station networks of terrestrial laser scanner data currently used for many valuable purposes such as 3D as-built rec...
In recent years, with the development of the high resolution data acquisition technologies, many different approaches and algorithms have been presented to extract the accurate and timely updated 3D m...
In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural d...
In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest pat...
Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpe...
Image segmentation is one of the most important methods for extracting information of interest from remote sensing image data, but it still remains some problems, leading to low quality segmentation. ...
In the last decades it often has been shown that Multilayer Perceptrons (MLPs) are powerful function approximators. They were successfully applied to a lot of different classification problems. Howev...

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