一种新的神经网络监督学习方法及其在土地覆盖分类中的应用

IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293) Pub Date : 1999-06-28 DOI:10.1109/IGARSS.1999.774633

A. Ohkubo, K. Niijima

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引用次数: 4

摘要

基于输入空间识别域的概念，提出了一种新的三层神经网络学习方法。神经网络通过最小化由域的几何性质导出的代价函数来学习。将这种学习方法应用于多波段数据的土地覆盖分类问题。

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A new supervised learning method of neural networks and its application to the land cover classification

Proposes a new learning method of three-layer neural networks based on the concept of domains of recognition in the input space. The neural network learns by minimizing a cost function which is derived from geometrical properties of the domain. This learning method is applied to land cover classification problems for multi-band data.

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IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293)

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