Jove
Visualize
联系我们

相关概念视频

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

[Effects of a glucocorticoid on development of kidney deficiency syndrome in a rat model of asthma].

Zhong xi yi jie he xue bao = Journal of Chinese integrative medicine·2010
Same author

[A case of respiratory epithelial adenomatoid hamartoma in nasal cavity.].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery·2010
Same author

[Construct cosmid libraries by isolating large genomic DNA fragments from Monascus ruber].

Wei sheng wu xue bao = Acta microbiologica Sinica·2010
Same author

Retinal tissue engineering using mouse retinal progenitor cells and a novel biodegradable, thin-film poly(e-caprolactone) nanowire scaffold.

Journal of ocular biology, diseases, and informatics·2010
Same author

[Correlation between MR diffusion weighted imaging with malignant degree of rabbit liver VX2 tumor models].

Zhonghua yi xue za zhi·2010
Same author

[Immune response in BALB/c mice immunized with BCG expressing HBV truncated C gene and preS1 gene].

Xi bao yu fen zi mian yi xue za zhi = Chinese journal of cellular and molecular immunology·2010
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

相关实验视频

Updated: Jun 7, 2025

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.8K

识别和量化河口的多种污染源,使用光谱和基于梯度的深度学习.

Zhuangming Zhao1, Min Xu2, Yu Yan2

  • 1South China Institute of Environmental Sciences, the Ministry of Ecology and Environment of PRC, Guangzhou 510655, China; Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519085, China.

Marine pollution bulletin
|November 17, 2024
PubMed
概括

一种新的智能方法使用深度学习来识别和量化河口的水污染源. 将激发发射矩阵 (EEM) 光光谱与梯度输入相结合,可以提高复杂水混合物的精度.

关键词:
卷积神经网络 (CNN) 是一种神经网络.深度学习是一种深度学习.河口的河口 河口光光谱学是一种光谱学.多种来源的污染污染.

更多相关视频

Fluorescently Labeled Bacteria as a Tracer to Reveal Novel Pathways of Organic Carbon Flow in Aquatic Ecosystems
09:35

Fluorescently Labeled Bacteria as a Tracer to Reveal Novel Pathways of Organic Carbon Flow in Aquatic Ecosystems

Published on: September 13, 2019

7.0K
Autofluorescence Imaging to Evaluate Red Algae Physiology
05:54

Autofluorescence Imaging to Evaluate Red Algae Physiology

Published on: February 17, 2023

1.3K

相关实验视频

Last Updated: Jun 7, 2025

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.8K
Fluorescently Labeled Bacteria as a Tracer to Reveal Novel Pathways of Organic Carbon Flow in Aquatic Ecosystems
09:35

Fluorescently Labeled Bacteria as a Tracer to Reveal Novel Pathways of Organic Carbon Flow in Aquatic Ecosystems

Published on: September 13, 2019

7.0K
Autofluorescence Imaging to Evaluate Red Algae Physiology
05:54

Autofluorescence Imaging to Evaluate Red Algae Physiology

Published on: February 17, 2023

1.3K

科学领域:

  • 环境科学 环境科学
  • 分析化学 分析化学
  • 数据科学数据科学数据科学

背景情况:

  • 河口地区面临来自多个来源的复杂水污染挑战.
  • 准确识别和量化这些来源对于有效的环境管理至关重要.
  • 传统的方法可能会与混合污染物的复杂光谱签名作斗争.

研究的目的:

  • 开发一种基于深度学习的智能方法,用于识别和量化河口环境中的水污染源.
  • 为了评估深度学习模型的不同输入数据类型的有效性.
  • 评估模型在各种混合污染和背景水组成条件下的性能.

主要方法:

  • 激发发射矩阵 (EEM) 光光谱对七个末端成员 (海水,雨水,五个污染源) 的表征.
  • 开发一个使用EME光谱的深度学习模型.
  • 使用原始EEM输入与组合EEM和梯度输入的模型性能比较.

主要成果:

  • 与单独使用EEM相比,EEM和梯度输入的组合显著提高了分类和定量准确性.
  • 尽管与更多混合污染源的准确性下降,但组合输入始终提高了3.1%至6.8%的性能.
  • 即使不到70%的海水和雨水,联合输入也实现了更高的准确性 (61.3%) 和较低的根平均平方误差 (11.4%),用于污染源比例估计.

结论:

  • 深度学习,特别是使用光谱和梯度数据的结合,提供了一种强大的方法来识别河口的水污染源.
  • 拟议的智能方法在复杂的河口水矩阵中显示出更高的准确性和稳定性.
  • 这种技术为环境监测和河口污染管理提供了宝贵的工具.