This paper proposes a semantic annotation conducted on a large number of scenes containing high resolution synthetic aperture radar (SAR) images. This investigation has an important impact in applications such as classification of urban areas, infrastructure, industrial sites, military sites, landscape and agriculture. The proposed taxonomy can serve as basis for building a semantic catalogue for Earth Observation (EO) images. Finally, a set of queries based on these semantics can be defined and are planned to be integrated into the new system developed at DLR
With the purpose of semantic extraction using TerraSAR-X dataset, in this paper, the problem has bee...
Very-high resolution (VHR) synthetic aperture radar (SAR) images from the last generation satellites...
In this paper, we describe an innovative content annotation method for high-resolution Synthetic Ape...
Users of remote sensing images analyzing land cover characteristics are very much interested in cla...
The amount of collected Earth Observation (EO) data is increasing immensely with a rate of several T...
The paper illustrates a technique how to semantically annotate high resolution SAR images to describ...
In this paper, we propose to identify the number of categories that can be retrieved from a very hig...
While the analysis and understanding of multispectral (i.e., optical) remote sensing images have mad...
We demonstrate how to achieve a semi-automated and rapid semantic annotation of high resolution SAR ...
In this article, we propose a new methodology used for annotating TerraSAR-X products in the data ba...
In this paper we propose to identify the number of urban categories that can be retrieved from very ...
Abstract—In this paper we propose to identify the number of urban categories that can be retrieved f...
Land cover mapping is one of the classic applications of synthetic aperture radar remote sensing. Ho...
This paper addresses the problem of High Resolution Synthetic Aperture Radar (SAR) image semantic an...
While the analysis and understanding of multispectral (i.e., optical) remote sensing images has made...
With the purpose of semantic extraction using TerraSAR-X dataset, in this paper, the problem has bee...
Very-high resolution (VHR) synthetic aperture radar (SAR) images from the last generation satellites...
In this paper, we describe an innovative content annotation method for high-resolution Synthetic Ape...
Users of remote sensing images analyzing land cover characteristics are very much interested in cla...
The amount of collected Earth Observation (EO) data is increasing immensely with a rate of several T...
The paper illustrates a technique how to semantically annotate high resolution SAR images to describ...
In this paper, we propose to identify the number of categories that can be retrieved from a very hig...
While the analysis and understanding of multispectral (i.e., optical) remote sensing images have mad...
We demonstrate how to achieve a semi-automated and rapid semantic annotation of high resolution SAR ...
In this article, we propose a new methodology used for annotating TerraSAR-X products in the data ba...
In this paper we propose to identify the number of urban categories that can be retrieved from very ...
Abstract—In this paper we propose to identify the number of urban categories that can be retrieved f...
Land cover mapping is one of the classic applications of synthetic aperture radar remote sensing. Ho...
This paper addresses the problem of High Resolution Synthetic Aperture Radar (SAR) image semantic an...
While the analysis and understanding of multispectral (i.e., optical) remote sensing images has made...
With the purpose of semantic extraction using TerraSAR-X dataset, in this paper, the problem has bee...
Very-high resolution (VHR) synthetic aperture radar (SAR) images from the last generation satellites...
In this paper, we describe an innovative content annotation method for high-resolution Synthetic Ape...