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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...
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Association Areas of the Cortex01:21

Association Areas of the Cortex

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Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
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Veins of Upper Limbs01:17

Veins of Upper Limbs

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The human circulatory system, a marvel of biological engineering, is a complex network of vessels that transport blood throughout the body. Among these, the veins responsible for carrying blood from the upper limbs are divided into two categories: deep and superficial.
The deep venous system is primarily composed of the ulnar and radial veins. The ulnar vein, which drains the fingers through the superficial palmar venous arches, and the radial vein, which serves the palms via the deep palmar...
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相关实验视频

Updated: May 5, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

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视觉特征引导的钻石卷积网络用于手指静脉识别

Qiong Yao1, Dan Song1, Xiang Xu1

  • 1Artificial Intelligence and Computer Vision Laboratory, Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China.

Sensors (Basel, Switzerland)
|September 28, 2024
PubMed
概括

一个新的视觉特征引导钻石卷积网络 (VF-DCN) 通过解决数据稀缺性和图像质量问题来增强手指静脉识别 (FVR). 这种方法以更少的参数实现了高精度和稳定性,提高了生物识别安全性.

科学领域:

  • 生物识别信息 生物识别信息
  • 计算机视觉 计算机视觉
  • 机器学习 机器学习

背景情况:

  • 指脉 (FV) 生物识别提供高安全性和非接触身份认证.
  • 现有的手指静脉识别 (FVR) 系统面临的挑战是有限的训练数据和不一致的图像质量.

研究的目的:

  • 引入一种新的卷积神经网络,即视觉特征引导的钻石卷积网络 (VF-DCN),以提高FVR系统的性能.
  • 通过创新的网络架构和无监督培训来解决FVR中的数据稀缺性和图像质量问题.

主要方法:

  • 开发了VF-DCN,这是一个使用Log-Gabor过器进行内核调整的多规模,多方向卷积神经网络.
  • 实现了以人类视觉为灵感的钻石形卷积内核架构,优化了跨尺度的过器分配.
  • 采用三层配置和完全无监督的培训,以实现简单性和性能.

主要成果:

  • 在四个不同的FV数据库中,VF-DCN实现了非常低的0.17%的等错率 (EER) 和高达100%的准确率 (ACC).
  • 与现有的FVR方法相比,证明了更高的识别准确性和稳定性.
  • 显示了减少的参数数量和较低的模型复杂性.

结论:

关键词:
记录采集器 (Log-Gabor) 是一个采集器.这是一个钻石卷积网络.手指静脉是指的静脉之一.视觉特征指导的视觉特征指导的视觉特征

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  • VF-DCN有效地克服了FVR系统的局限性,提供了高精度和稳定性.
  • 拟议的网络架构和培训策略为安全和高效的生物识别身份验证提供了一个有希望的解决方案.
  • VF-DCN提供了一种计算效率高,准确度高的指纹静脉识别方法.