基于神经网络集成的多光谱图像分类

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2016-02-01 DOI:10.1109/ICACI.2016.7449838

Xiaoyang Fu

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引用次数: 1

摘要

本文研究了神经网络集成分类器及其在多光谱图像分类中的应用。在SPOT多光谱图像数据上验证了NNE分类器的有效性。通过与贝叶斯最大似然分类器、k-NN分类器等标准分类器的比较，表明NNE分类器在多光谱图像分类上具有更好的性能。

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Multispectral image classification based on neural network ensembles

In this paper, we investigate neural network ensemble (NNE) classifier and its application to multi-spectral image classification. The effectiveness of the NNE classifier is demonstrated on SPOT multi-spectral image data. Compared with standard classifiers, such as Bayes maximum-likelihood classifier, k-NN classifier, it has shown that the NNE classifier can have better performance on multi-spectral image classification.

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2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)

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