Comparison of maximum likelihood classification method with supervised artificial neural network algorithms for land use activities-Reference-Cited by-同舟云学术

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Comparison of maximum likelihood classification method with supervised artificial neural network algorithms for land use activities

Published:2004-05 Issue:9 Volume:25 Page:1733-1748
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Erbek F. Sunar¹,Özkan C.²,Taberner M.³

Affiliation:

1. a Istanbul Technical University , Civil Engineering Faculty, Remote Sensing Division , Istanbul, 80626 Turkey

2. b Erciyes University , Geodesy and Photogrammetry Department , Kayseri, 38039 Turkey

3. c University of Bristol , Department of Geography , University Road, BS8 1SS, UK

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/0143116031000150077

Reference35 articles.

1. Neural Network Approaches Versus Statistical Methods In Classification Of Multisource Remote Sensing Data

2. Finding optimal neural networks for land use classification

3. Bridle J. S 1990 Probabilistic interpretation of feedforward classification network outputs, with relations to statistical pattern recognition InNeurocomputing: Algorithms, Architectures and Applications(Berlin: Springer-Verlag)

4. An iterative technique for the detection of land-cover transitions in multitemporal remote-sensing images

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