Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

695
When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
695
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.1K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.1K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Generation and reconfiguration of dual-band infrared plasmonic slit resonances from nano-kirigami structures.

Optics express·2026
Same author

Nano-opto-electro-mechanical nano-kirigami metasurface for on-chip dynamic spectral shaping.

Optics express·2026
Same author

Bio-inspired small target detecting visual neural network with motion direction decoding compensation in large scene.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Mid-Wave Infrared Polarization Combiner Based on Reflective Metasurface.

Micromachines·2026
Same author

A deep learning framework for predicting aircraft trajectories from sparse satellite observations.

Scientific reports·2025
Same author

Absorption-enhanced nanopillar-arrayed Na<sub>2</sub>KSb photocathode for improving image intensifier performance.

Optics express·2025

相关实验视频

Updated: Jul 2, 2025

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

2.5K

一个基于深度学习的三阶段培训框架,用于频谱基线校正.

Qingliang Jiao1,2, Boyong Cai1,2, Ming Liu1,2

  • 1Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China. bit411liu@bit.edu.cn.

Analytical methods : advancing methods and applications
|February 19, 2024
PubMed
概括

这项研究引入了一种新的深度学习方法,用于光谱基线校正,减少对广泛配对数据的需求. 该方法通过提高U-net性能和采用独特的三阶段培训框架来提高光谱分析的准确性.

更多相关视频

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.0K
Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research
08:12

Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research

Published on: February 16, 2024

9.3K

相关实验视频

Last Updated: Jul 2, 2025

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

2.5K
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.0K
Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research
08:12

Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research

Published on: February 16, 2024

9.3K

科学领域:

  • 频谱学是一种光谱学.
  • 化学测量 化学测量 化学测量
  • 机器学习 机器学习

背景情况:

  • 频谱数据的基线偏移显著影响测量准确性和定量分析.
  • 深度学习为光谱基线校正提供了强大的解决方案,但受到大型配对数据要求和数据采集挑战的阻碍.

研究的目的:

  • 开发一种强大的深度学习方法,用于光谱基线校正,克服数据限制.
  • 为了提高U-net架构的性能,用于光谱数据处理.
  • 为了减少对广泛的配对光谱数据集的依赖,培训.

主要方法:

  • 一个新的学习特征融合 (LFF) 模块被设计成通过自适应地整合多尺度特征来提高U-net性能.
  • 提出了三阶段的培训框架:第一阶段使用airPLS进行初始数据精制,第二阶段使用合成光谱生成,第三阶段使用对比学习来弥合合成和真实光谱数据的差距.

主要成果:

  • 拟议的LFF模块显著提高了U-net处理光谱基线校正的能力.
  • 三阶段培训框架有效地减少了对大型,配对的光谱数据集的依赖.
  • 实验结果证明了该方法作为基线校正的强大工具的有效性.

结论:

  • 开发的深度学习方法为光谱基线校正提供了有效的解决方案,解决了关键数据限制.
  • 该方法显示了改善光谱定量分析和相关应用的巨大潜力.