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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...
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. ...
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...
Automatic building extraction remains an open research area in digital photogrammetry. While many algorithms have been proposed for building extraction, none of them solve the problem completely. This...
Position information obtained from standard GPS receivers is known to be corrupted with noise. To make effective use of GPS information in a navigation system it is essential to model this noise and t...
In this paper the implementation and the functionality of software created on the basis of neural networks technology is explained.The program developed allows the user to read an image, to create and...
This paper presents a methodology for simulating urban growth phenomenon through utilizing remote sensing imagery and neural network (NN) algorithms. Historical satellite images of Indianapolis city, ...
Illegal oil spill discharges cause serious damage to marine ecosystems. Synthetic Aperture Radar (SAR) images are extensively used for the detection of oil spills in the marine environment, as they ...
In this paper, the concepts of wavelet analysis and neural networks are applied to the classification of shuttle imaging radar experiment C (SIR-C) synthetic aperture radar (SAR) data from a location ...
The aim of this paper is to describe a potential on-board change detection chain by earth observation satellites (optical and SAR). The benefits of such an on-board chain are multiple : reduction of ...
URBAN SIMULATION USING NEURAL NETWORKS AND CELLULAR AUTOMATA FOR LAND USE PLANNING.
Object recognition has been the focus of much research in the photogrammetric and image processing communities. The goal of this research is often the quantitative three-dimensional measurement of obj...
This paper presents classification results using neural networks based on INSAR coherence imagery data for evaluation of the damage of Kobe earthquake in 1995. Coherence derived from multi-temporal SA...

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