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IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
911

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功能从基于多值二进制的多光谱遥感图像中提取特征.

Bohdan Rusyn1,2, Oleksiy Lutsyk3, Rostyslav Kosarevych1

  • 1Department of Remote Sensing Information Technologies, Karpenko Physico-Mechanical Institute, NAS of Ukraine, Lviv, Ukraine.

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科学领域:

  • 计算机科学 计算机科学
  • 遥感 遥感 遥感 遥感
  • 机器学习 机器学习

背景情况:

  • 由于计算需求,深度卷积神经网络 (CNN) 在实时应用中面临限制.
  • 遥感图像分类需要有效的模型来及时分析.

研究的目的:

  • 为实时遥感图像分类提出一个高效的解决方案.
  • 为了克服深度CNN模型的计算局限性.

主要方法:

  • 在多光谱遥感图像上使用多值二元化.
  • 为分类提取歧视性特征.
  • 将拟议的方法与ResNet和Ensemble CNN模型在准确性和训练时间方面进行比较.

主要成果:

  • 拟议的方法在小数据集上显示出卓越的准确性.
  • 它在更大的数据集上保持了与深度CNN模型相比较的回忆得分.
  • 在所有数据集大小中实现了约5倍的培训和推断时间.

结论:

  • 多值二元化为远程传感图像分类提供了一个计算效率高的替代方案.
  • 该方法平衡了准确性和显著的速度改进,使其适合实时应用.