This paper shortly presents a project lanced by the Computer Science Department of the "1 Decembrie 1918" University of Alba Iulia. The project is based on the increasing amount and complexity of the earth science data collected by remote sensors. This huge amount of information underscores the need for research into strategies and techniques to facilitate its analysis and understanding. In this project an application of artificial neural networks to human-centered earth science information processing is described
In this article the outcomes of investigations on learning dynamics of a top-soil with application...
The Earth remote sensing is becoming a new and quickly developing multiscience area of a practical i...
Mineral exploration is a complex task that often requires the use of satellite imagery, geochemical ...
Artificial neural networks are computational models widely used in geospatial analysis for data clas...
The following paper gives an introduction to advanced computer graphics systems and describes a new ...
The following paper gives an introduction to advanced computer graphics systems and describes a new ...
Abstract-Neural nets offer the potential to classify data based upon a rapid match to overall patter...
A new method for remotely sensed change detection based on artificial neural networks is presented. ...
Sensors mounted on satellite platforms are well-known and useful tools to observe the surface of the...
Earth observation and monitoring of soil quality, long term changes of soil characteristics and dete...
Thesis (Ph.D.)--Boston UniversityAdvances in remote sensing and associated capabilities are expected...
An artificial neural network approach was evaluated in multispectral image processing applications, ...
Artificial neural networks are an interesting method for modelling phenomena, including spatial phen...
Upland vegetation represents an important resource that requires frequent monitoring. However, the h...
This paper proposes the application of structured neural networks to land-cover classification in re...
In this article the outcomes of investigations on learning dynamics of a top-soil with application...
The Earth remote sensing is becoming a new and quickly developing multiscience area of a practical i...
Mineral exploration is a complex task that often requires the use of satellite imagery, geochemical ...
Artificial neural networks are computational models widely used in geospatial analysis for data clas...
The following paper gives an introduction to advanced computer graphics systems and describes a new ...
The following paper gives an introduction to advanced computer graphics systems and describes a new ...
Abstract-Neural nets offer the potential to classify data based upon a rapid match to overall patter...
A new method for remotely sensed change detection based on artificial neural networks is presented. ...
Sensors mounted on satellite platforms are well-known and useful tools to observe the surface of the...
Earth observation and monitoring of soil quality, long term changes of soil characteristics and dete...
Thesis (Ph.D.)--Boston UniversityAdvances in remote sensing and associated capabilities are expected...
An artificial neural network approach was evaluated in multispectral image processing applications, ...
Artificial neural networks are an interesting method for modelling phenomena, including spatial phen...
Upland vegetation represents an important resource that requires frequent monitoring. However, the h...
This paper proposes the application of structured neural networks to land-cover classification in re...
In this article the outcomes of investigations on learning dynamics of a top-soil with application...
The Earth remote sensing is becoming a new and quickly developing multiscience area of a practical i...
Mineral exploration is a complex task that often requires the use of satellite imagery, geochemical ...