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相关概念视频

IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

794
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...
794
Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

297
Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
297
IR Spectrum01:19

IR Spectrum

947
When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
Transmittance is defined as the ratio of the radiant power passing through a sample to that from the radiation's source. Multiplying the transmittance by 100 gives the percent transmittance (%T), which varies between 100% (no absorption) and 0%...
947

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相关实验视频

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研究基于太赫兹成像技术的小麦杂质识别方法.

Guangming Li1, Hongyi Ge1, Yuying Jiang2

  • 1Key Laboratory of Grain Information Processing and Control (Henan University of Technology), Ministry of Education, Zhengzhou 450001, China; Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Zhengzhou, 450001, China; College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
|September 30, 2024
PubMed
概括
此摘要是机器生成的。

一个新的人工蜂鸟算法-RetinaNet-X (AHA-RetinaNet-X) 模型与太赫兹 (THz) 成像相结合,可以快速,非破坏性地检测小麦杂质. 这种先进的方法准确地分类小麦和杂质,改善质量评估.

关键词:
人工蜂鸟算法的人工蜂鸟算法网红网 (RetinaNet) 是一个网络.目标检测 目标检测特拉赫兹成像成像技术小麦杂质 小麦杂质

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科学领域:

  • 农业科学 农业科学
  • 图像技术技术的成像技术
  • 人工智能的人工智能

背景情况:

  • 传统的小麦杂质检测方法是不精确的,缓慢的,劳动密集的.
  • 准确的小麦质量评估至关重要,并依赖于有效的杂质检测.
  • 特拉赫兹 (THz) 技术为材料分析提供快速,非破坏性和透性成像.

研究的目的:

  • 开发一种快速而准确的方法,使用THz成像来检测和分类小麦中的杂质.
  • 引入和评估用于小麦和杂质识别的AHA-RetinaNet-X算法.
  • 通过非接触性,非破坏性分析,提高小麦质量分类.

主要方法:

  • 使用THz三维断层扫描成像系统捕获小麦和杂质的图像.
  • 开发了一个新的分类和识别算法,AHA-RetinaNet-X,将RetinaNet与人工蜂鸟算法 (AHA) 集成.
  • 在两个不同的THz图像数据集上训练并验证了模型:一个用于小麦/杂质分类,另一个用于杂质分类.

主要成果:

  • AHA-RetinaNet-X模型在准确性,F1得分,精度,回忆和特异性方面表现出比其他模型更好的表现.
  • 实现了高准确率 (例如,小麦/杂质数据集的96.1%,杂质数据集的95.6%).
  • 该模型达到92.1%的平均平均精度 (mAP),表现优于比较模型.

结论:

  • 整合THz成像和AHA-RetinaNet-X算法提供了一种有效的新方法,用于非接触式,快速和非破坏性地检测小麦杂质.
  • 这种方法显著提高了小麦质量评估的准确性和效率.
  • 这些发现为开发其他物质类似检测和识别方法提供了宝贵的参考.