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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...
Remote sensing has been increasingly used to derive land cover information by manual interpretation or automated classification. As promising automated classifiers, artificial neural networks are diff...
In this paper we report the results of a pilot project we conduct to develop a semi-automated approach for tidal stream network extraction from remote sensor data. Our test site is part of the North I...

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