全体发言嘉宾1:连续统融合:一种新的推理理论

2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing Pub Date : 2010-06-14 DOI:10.1109/WHISPERS.2010.5594828

A. Schaum

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引用次数: 0

摘要

通过以模型的形式利用人类的洞察力，复合假设(CH)测试方法可以生成比替代的“数据驱动方法”更强大的决策算法，具有更强的泛化能力。后者包括人工神经网络、遗传算法、支持向量机等。

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Plenary speaker 1: Continuum fusion: A new theory of inference

By exploiting human insight in the form of a model, methods of composite hypothesis (CH) testing can generate more robust decision algorithms, with a greater ability to generalize, than the alternative “data-driven methods.” The latter include artificial neural networks, genetic algorithms, support vector machines, etc.

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来源期刊

2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

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