Radial basis function neural networks classification using very high spatial resolution satellite imagery: an application to the habitat area of Lake Kerkini (Greece)-Reference-Cited by-同舟云学术

Radial basis function neural networks classification using very high spatial resolution satellite imagery: an application to the habitat area of Lake Kerkini (Greece)

Published:2005-05-01 Issue:9 Volume:26 Page:1861-1880
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Keramitsoglou I.¹,Sarimveis H.²,Kiranoudis C. T.²,Sifakis N.³

Affiliation:

1. a University of Athens , Department of Applied Physics , Building PHYS‐V, GR‐15784, Athens, Greece

2. b School of Chemical Engineering , National Technical University of Athens , Zografou Campus, GR‐15780 Athens, Greece

3. c Institute for Space Applications and Remote Sensing , National Observatory of Athens , Metaxa & Vas. Pavlou St, Penteli, GR‐15236 Athens, Greece

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431160512331326594

Reference23 articles.

1. Classification of ASAS multiangle and multispectral measurements using artificial neural networks

2. Design of neural networks for classification of remotely sensed imagery

3. Probabilistic neural network architecture for high-speed classification of remotely sensed imagery

4. Application of neural networks to terrain classification

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