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

Types Of Transformers01:16

Types Of Transformers

1.6K
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
1.6K
Masking and Demasking Agents01:19

Masking and Demasking Agents

4.1K
EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...
4.1K
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

739
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
739

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

Tensile strength suppresses the osteogenesis of periodontal ligament cells in inflammatory microenvironments.

Molecular medicine reports·2017
Same author

A PDGFB mutation causes paroxysmal nonkinesigenic dyskinesia with brain calcification.

Movement disorders : official journal of the Movement Disorder Society·2017
Same author

A Molecular Switch Regulating Cell Fate Choice between Muscle Progenitor Cells and Brown Adipocytes.

Developmental cell·2017
Same author

Microarray analysis of differentially expressed genes and their functions in omental visceral adipose tissues of pregnant women with vs. without gestational diabetes mellitus.

Biomedical reports·2017
Same author

Development and validation of a simplified titration method for monitoring volatile fatty acids in anaerobic digestion.

Waste management (New York, N.Y.)·2017
Same author

Association Analysis of Nonsyndromic Congenital Heart Disease and Tag Single Nucleotide Polymorphisms of TBX20 and Genes in the Ras-MAPK Pathway.

Genetic testing and molecular biomarkers·2017

相关实验视频

Updated: May 1, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

6.9K

带有动态令牌集群的等级图交互变压器用于伪装对象检测.

Siyuan Yao, Hao Sun, Tian-Zhu Xiang

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |October 15, 2024
    PubMed
    概括

    这项研究介绍了HGINet,这是一个用于伪装物体检测 (COD) 的新型网络. 通过使用层次图交互来改善特征区分,HGINet有效地识别隐藏在复杂背景中的对象.

    科学领域:

    • 计算机视觉 计算机视觉
    • 人工智能的人工智能
    • 机器学习 机器学习

    背景情况:

    • 伪装物体检测 (COD) 是具有挑战性的,因为物体与背景无融合.
    • 现有的方法难以准确地区分伪装物体与周围环境.

    研究的目的:

    • 提出一种新的等级图交互网络 (HGINet),以改进伪装对象的检测.
    • 通过利用层次的标记化特征和图形交互来增强发现不可察觉对象的能力.

    主要方法:

    • 区域意识的令牌聚焦注意力 (RTFA) 具有动态令牌集群来识别可区分的令牌.
    • 层次图交互变压器 (HGIT) 用于层次特征之间的双向通信.
    • 解码器网络带有信心聚合特征融合 (CAFF) 模块,用于在模两可的区域中改进细节.

    主要成果:

    • 与基准数据集 (COD10K,CAMO,NC4K,CHAMELEON) 上的最先进的方法相比,HGINet表现出更高的性能.
    • 拟议的网络通过增强视觉语义和完善局部细节,有效地区分伪装对象.

    结论:

    • 在伪装物体检测方面,HGINet提供了显著的进步.

    更多相关视频

    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
    04:23

    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

    Published on: April 21, 2023

    1.8K
    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

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

    Published on: December 15, 2023

    478

    相关实验视频

    Last Updated: May 1, 2026

    Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
    12:27

    Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

    Published on: February 15, 2017

    6.9K
    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
    04:23

    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

    Published on: April 21, 2023

    1.8K
    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

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

    Published on: December 15, 2023

    478
  • 层次图交互方法有效地解决了检测具有低区分能力的对象的挑战.