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Updated: Jun 30, 2025

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
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在地质上受限制的GANomaly网络用于通过频域训练数据的频域预测绘图

Hamid Sabbaghi1, Seyed Hassan Tabatabaei2, Nader Fathianpour2

  • 1Department of Mining Engineering, Isfahan University of Technology, Isfahan, Iran. h.sabbaghi@mi.iut.ac.ir.

Scientific reports
|March 15, 2024
PubMed
概括

一个新的地质约束GANomaly模型有效地识别了矿产勘探的多元素地化学异常. 与传统方法相比,这种深度学习方法显著提高了检测黄金-铜发生的准确性.

关键词:
在AuCu矿物化中.频率域数据数据频率域数据生成性的对抗性网络.在地质上受到限制的GAN异常.矿产 prospektivity 绘制矿产的前景性地图.多元素地质化学异常

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