Land cover classification using artificial neural networks Abstract This Diploma thesis deals with automatic classification of the satellite high spatial resolution image in the field of land cover. The first half of the work contains the theoretical information about remote sensing and classification methods. The biggest attention is given to the artificial neural networks. In practical part of Diploma thesis are these methods used for the classification of SPOT satellite image. Keywords: remote sensing, image classification, artificial neural networks, SPO
Sensors mounted on satellite platforms are well-known and useful tools to observe the surface of the...
The thematic maps derived from remotely-sensed images are invaluable sources of information for vari...
The increasing number of satellite missions providing more and more data for updating land cover and...
Cieľom tejto práce je klasifikácia družicových snímok pomocou umelých neurónových sietí za účelom ro...
This paper describes the application of artificial neural networks (ANN) towards the supervised clas...
Artificial Neural Network (ANN) is an important Artificial Intelligence (AI) and Machine Learning (M...
This paper presents a method for classifying Landsat Satellite Images. This method is based on the S...
Landcover classification using automated classification techniques, while employing remotely sensed ...
Accurate and updated land cover maps provide crucial basic information in a number of important ente...
Remote sensing has been widely used to obtain land cover information using automated classification....
Land-Cover classification of mountain ecosystem using image data with different spatial and spectral...
Land cover analysis plays an important role in many environmental applications nowadays. Satellite i...
The resolution of remote sensing images increase every day.Most of the existing methods is used the ...
U teorijskom dijelu ovog rada objašnjen je problem raspoznavanja tipa terena, te su opisani postupci...
With the recent launch of MERIS, a wide range of new possibilities for the periodic land cover chara...
Sensors mounted on satellite platforms are well-known and useful tools to observe the surface of the...
The thematic maps derived from remotely-sensed images are invaluable sources of information for vari...
The increasing number of satellite missions providing more and more data for updating land cover and...
Cieľom tejto práce je klasifikácia družicových snímok pomocou umelých neurónových sietí za účelom ro...
This paper describes the application of artificial neural networks (ANN) towards the supervised clas...
Artificial Neural Network (ANN) is an important Artificial Intelligence (AI) and Machine Learning (M...
This paper presents a method for classifying Landsat Satellite Images. This method is based on the S...
Landcover classification using automated classification techniques, while employing remotely sensed ...
Accurate and updated land cover maps provide crucial basic information in a number of important ente...
Remote sensing has been widely used to obtain land cover information using automated classification....
Land-Cover classification of mountain ecosystem using image data with different spatial and spectral...
Land cover analysis plays an important role in many environmental applications nowadays. Satellite i...
The resolution of remote sensing images increase every day.Most of the existing methods is used the ...
U teorijskom dijelu ovog rada objašnjen je problem raspoznavanja tipa terena, te su opisani postupci...
With the recent launch of MERIS, a wide range of new possibilities for the periodic land cover chara...
Sensors mounted on satellite platforms are well-known and useful tools to observe the surface of the...
The thematic maps derived from remotely-sensed images are invaluable sources of information for vari...
The increasing number of satellite missions providing more and more data for updating land cover and...