One of the problems in the thematic interpretation of the remote sensor (RS) data is the processing of the sets of multispectral, multydate images. The problem is that when we try to compare two and more RS image, we have to rectify their geometry and correct atmospheric effects. While the geometric correction could be done with any precision, the atmospheric correction for a set of images is a very complex task, and it could not be solved in a common case. We propose a new approach, based on the artificial neural networks, for a stable RS images classification and interpretation without the atmospheric correction. That approach, using the Kohonen's Self-Organized Maps (SOM), has been realized as a part of the ScanEx image processing techno...
In recent years, the remote-sensing community has became very interested in applying neural networks...
This paper is of classification of remote sensed Multispectral satellite images using supervised and...
A Neural network with topology 2-8-8 is evaluated against the standard of supervised non-parametric ...
One of the problems in the thematic interpretation of the remote sensor (RS) data is the processing ...
Abstract. In this paper we investigate the performance of the Koho-nen’s self organizing map (SOM) a...
Unlike conventional unsupervised classification methods, such as K-means and ISODATA, which are base...
Classification of remotely sensed multispectral images involves assigning a class to each pixel whic...
The current paper discusses the importance of the modern high resolution satellite imagery. The acqu...
We study the application of self-organizing maps (SOMs) for the analyses of remote sensing spectral ...
To improve the accuracy of remote sensing image classification based on a self-organizing competitiv...
This paper proposes the application of structured neural networks to classification of multisensor r...
This paper proposes the application of Structured Neural Networks to the supervised classification o...
Abstract- This paper proposes the application of structured neural networks to classification of mul...
Abstract: — The objective of this paper is to utilize the features obtained by the artifical neural ...
The following paper describes the application of self-organizing neural networks on the analysis and...
In recent years, the remote-sensing community has became very interested in applying neural networks...
This paper is of classification of remote sensed Multispectral satellite images using supervised and...
A Neural network with topology 2-8-8 is evaluated against the standard of supervised non-parametric ...
One of the problems in the thematic interpretation of the remote sensor (RS) data is the processing ...
Abstract. In this paper we investigate the performance of the Koho-nen’s self organizing map (SOM) a...
Unlike conventional unsupervised classification methods, such as K-means and ISODATA, which are base...
Classification of remotely sensed multispectral images involves assigning a class to each pixel whic...
The current paper discusses the importance of the modern high resolution satellite imagery. The acqu...
We study the application of self-organizing maps (SOMs) for the analyses of remote sensing spectral ...
To improve the accuracy of remote sensing image classification based on a self-organizing competitiv...
This paper proposes the application of structured neural networks to classification of multisensor r...
This paper proposes the application of Structured Neural Networks to the supervised classification o...
Abstract- This paper proposes the application of structured neural networks to classification of mul...
Abstract: — The objective of this paper is to utilize the features obtained by the artifical neural ...
The following paper describes the application of self-organizing neural networks on the analysis and...
In recent years, the remote-sensing community has became very interested in applying neural networks...
This paper is of classification of remote sensed Multispectral satellite images using supervised and...
A Neural network with topology 2-8-8 is evaluated against the standard of supervised non-parametric ...