...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE sensors journal >A Bayesian Approach to Binary Classification of Mid-Infrared Spectral Data With Noisy Sensors
【24h】

A Bayesian Approach to Binary Classification of Mid-Infrared Spectral Data With Noisy Sensors

机译：嘈杂传感器中红外光谱数据二进制分类的贝叶斯探讨

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The problem of classifying substances using MIR laser and sensors with low signal-to-noise ratio remains challenging. The existing methods rely largely on using lasers at multiple wavelengths and expensive high quality sensors. We propose and demonstrate a statistical method that classifies spectral data generated from MIR imaging spectroscopy experiments using few wavelengths and inexpensive detector arrays while still achieving high accuracy. Results with quantifiable analytic performance are obtained by attributing probability distribution functions to the images obtained and implementing a binary decision process. Our method can provide a solution with as few as a single measurement and allows the use of low SNR sensors. This can increase throughput and lower costs on security checkpoints, pharmaceutical production monitoring, industrial quality control, and similar applications.
机译：使用MIR激光器和具有低信噪比的传感器对物质进行分类的问题仍然具有挑战性。现有方法在很大程度上依赖于多个波长和昂贵的高质量传感器的激光器。我们提出并展示了一种统计方法，其通过少量波长和廉价的探测器阵列来分类由MIR成像光谱实验产生的谱数据，同时仍然实现高精度。通过归因于获得的图像和实现二进制决策过程的概率分布函数来获得可量化的分析性能的结果。我们的方法可以提供与单一测量只有少量的解决方案，并允许使用低SNR传感器。这可以提高吞吐量和降低安全检查点，药品生产监测，工业质量控制和类似应用的成本。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号