一种用于深海热图分类的模块化神经结构

Proceedings of OCEANS '93 Pub Date : 1993-10-18 DOI:10.1109/OCEANS.1993.325963

Y. Stephan, B. Frachon

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引用次数: 1

摘要

提出了一种深度热图分类的神经方法。多层感知器(MLP)的模块化架构源于预分类成五种主要类型的温度分布。类型和类是从预先建立的类型中发出的。在红海剖面数据库上对该方法的性能进行了评价。结果表明，该方法是有效的，但存在类重叠的问题。

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A modular neural architecture for bathythermograms classification

Presents a neural approach for bathythermogram classification. A modular architecture of multi-layer perceptrons (MLP) stemming from a preclassification into five main types of temperature profile is used. The types and classes are issued from a pre-established typology. The performance of this approach is evaluated on a Red Sea profiles database. The results show that the method is efficient but suffers from classes overlapping.<>

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Proceedings of OCEANS '93

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