An unsupervised method of classifying remotely sensed images using Kohonen self‐organizing maps and agglomerative hierarchical clustering methods-Reference-Cited by-同舟云学术

An unsupervised method of classifying remotely sensed images using Kohonen self‐organizing maps and agglomerative hierarchical clustering methods

Published:2008-05-19 Issue:11 Volume:29 Page:3171-3207
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Gonçalves M. L.¹,Netto M. L. A.²,Costa J. A. F.³,Zullo Júnior J.⁴

Affiliation:

1. a Department of Computer Science , Pontifical Catholic University of Minas Gerais , Av. Padre Francis Cletus Cox, 1661, 37701‐355, Poços de Caldas, MG, Brazil

2. b School of Electrical and Computer Engineering , State University of Campinas , SP, Brazil

3. c Department of Electrical Engineering , Federal University of Rio Grande do Norte , Natal, RN, Brazil

4. d Agrometeorology Research Center , State University of Campinas , SP, Brazil

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431160701442146

Reference98 articles.

1. A supervised Thematic Mapper classification with a purification of training samples

2. Introduction Neural networks in remote sensing

3. Improving the performance of classifiers in high-dimensional remote sensing applications: an adaptive resampling strategy for error-prone exemplars (ARESEPE)

4. A clustering technique for summarizing multivariate data

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