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相关概念视频

IR Spectrometers01:25

IR Spectrometers

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There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
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相关实验视频

Updated: Jul 1, 2025

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
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通过RGB-IR跨模态图像生成增强红外光流网络计算.

Feng Huang1, Wei Huang1, Xianyu Wu1

  • 1School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China.

Sensors (Basel, Switzerland)
|March 13, 2024
PubMed
概括
此摘要是机器生成的。

研究人员开发了一种新的方法来生成红外 (IR) 光流数据集. 这克服了用于IR图像分析的深度学习的局限性,将其应用扩展到RGB图像之外.

关键词:
深度神经网络是一个神经网络.红外图像中的红外图像.光学流的光学流量

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科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 红外成像技术 红外成像技术

背景情况:

  • 目前对光流的深度学习仅限于RGB图像,因为捕获真实红外 (IR) 光流具有挑战.
  • 这限制了光学流量计算在IR领域的应用和研究.

研究的目的:

  • 提出一种方法来生成一个光流数据集,专门用于IR图像.
  • 在红外图像上实现基于深度学习的光流计算.

主要方法:

  • 使用RGB-IR跨模态图像转换网络,基于改进的Pix2Pix实现.
  • 通过使用M3FD RGB-IR对齐的双模式数据集验证了转换网络.
  • 将转换应用于KITTI RGB光流数据集,以生成用于训练的IR图像.

主要成果:

  • 使用转换的IR图像训练了一个光流计算网络.
  • 在训练IR数据之前和之后分析了光流网络的性能.
  • 证明了生成和使用红外光流数据集的可行性.

结论:

  • 拟议的方法通过转换现有的RGB数据集,成功生成了IR光流数据集.
  • 这种方法扩大了深度学习应用的范围,用于将光流计算扩展到红外频谱.
  • 该研究为基于IR的计算机视觉任务的未来研究提供了基础.