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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...
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...
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. ...
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...
The concept of research was based on the selection of several representations, which later were correlated by means of classic, and neural methods. In the course of research, classic methods of image ...
The use of non-metric digital cameras in close-range photogrammetric applications and machine vision has become a popular research agenda. Being an essential component of photogrammetric evaluation, ...
This paper presents a novel method for detecting ships from high-resolution synthetic aperture radar (SAR) images. This method categorizes ship targets from single-pol SAR images using texture feature...
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, ...

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