APPLICATION OF AN ARTIFICIAL NEURAL NETWORK FOR AIRBORNE MAGNETIC DATA DISCRIMINATION
APPLICATION OF AN ARTIFICIAL NEURAL NETWORK FOR AIRBORNE MAGNETIC DATA DISCRIMINATION
复制标题
DOI：
10.4133/1.3614179
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Jeannie Norton;J. Sheehan;L. Beard
中科院分区：
文献类型：
--
作者：
Jeannie Norton;J. Sheehan;L. Beard
这项工作的目的是开发和应用人工神经网络(ANN)来根据来自机载垂直磁梯度数据的输入来区分军械和非军械。该项目评估了更多的产出分类是否有益和/或需要进行有效和一致的区分，例如大军械、小军械、废料和地质。虽然最终有可能使用神经网络确定军械类型，但对于这个项目，我们使用基本分类方案获得了最好的结果：UXO或非UXO。
The objective of this work was to develop and apply an artificial neural network (ANN) to discriminate ordnance from non-ordnance based on input derived from airborne vertical magnetic gradient data. The project assessed whether more output classifications are beneficial and/or required for effective and consistent discrimination, e.g. large ordnance, small ordnance, scrap, and geology. While it may ultimately be possible to determine ordnance type using ANNs, for this project we got best results with the fundamental classification scheme: UXO or not UXO.