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相关概念视频

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...
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Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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相关实验视频

Updated: May 6, 2026

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
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基于深度卷积下降反转断层扫描的指纹认证.

Shuainan Chen1, Chengwei Zhao1, Jiahao Ren1

  • 1State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China.

Ultrasonics
|June 1, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种使用Lamb波和深度学习的新型指纹认证系统. 该方法提高了准确性和速度,克服了湿手指和错误细节检测的挑战.

关键词:
深度快速倒置断层扫描 (DFT) 是一种快速倒置断层扫描.指纹验证验证的真实性指纹的反转是指纹的反转.羊羔的波浪在浪叫着.面具 R-CNN 的意思

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科学领域:

  • 生物识别信息 生物识别信息
  • 信号处理 信号处理
  • 机器学习 机器学习

背景情况:

  • 传统的指纹认证与湿手指和虚假细节作斗争.
  • 现有的方法需要高效的特征提取和匹配,以便可靠的识别.

研究的目的:

  • 开发使用Lamb波和深度学习的快速指纹反转和身份验证方法.
  • 提高指纹识别的准确性和稳定性,特别是在具有挑战性的条件下.

主要方法:

  • 深度学习与指纹分析的多尺度融合的整合.
  • 使用深度快速反转断层扫描 (DeepFIT) 进行加速的超声波阵列重建和微小的反转.
  • 使用Mask R-CNN对多尺度指纹特征进行细分和匹配.

主要成果:

  • 通过抑制的文物实现了亚毫米级指纹微小的反转.
  • 通过提取有意义的细节,在身份验证中证明了提高准确性和可靠性.
  • 在拟议的指纹认证过程中验证了高准确性,稳定性和速度.

结论:

  • 开发的方法通过解决现有技术的局限性来优化指纹身份验证.
  • 深度学习集成显著提高了指纹识别系统的性能.
  • 该方法为安全和高效的生物识别提供了一个有希望的解决方案.