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

Masking and Demasking Agents01:19

Masking and Demasking Agents

2.5K
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...
2.5K
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

293
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
293
Convolution Properties II01:17

Convolution Properties II

235
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
235
Convolution Properties I01:20

Convolution Properties I

183
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
183
Deconvolution01:20

Deconvolution

190
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
190

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 electroacupuncture at "Neiguan" (PC 6) on p38 MAPK signaling pathway in rats with cardiac hypertrophy].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion·2012
Same author

Accurate measurement of oxygen consumption in children undergoing cardiac catheterization.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions·2012
Same author

Glutathione S-transferase polymorphisms and bone tumor risk in China.

Asian Pacific journal of cancer prevention : APJCP·2012
Same author

Systemic oxygen transport derived by using continuous measured oxygen consumption after the Norwood procedure-an interim review.

Interactive cardiovascular and thoracic surgery·2012
Same author

Discovery and optimization of 2,4-diaminoquinazoline derivatives as a new class of potent dengue virus inhibitors.

Journal of medicinal chemistry·2012
Same author

β(3)-Adrenoceptor Antagonist SR59230A Attenuates the Imbalance of Systemic and Myocardial Oxygen Transport Induced by Dopamine in Newborn Lambs.

Clinical Medicine Insights. Cardiology·2012

相关实验视频

Updated: Jul 21, 2025

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction
06:19

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

Published on: August 16, 2024

449

MagConv:面具引导的卷积用于图像绘制.

Xuexin Yu, Long Xu, Jia Li

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |July 28, 2023
    PubMed
    概括

    面具引导卷积 (MagConv) 通过在图像和面具路径之间启用共享内核来改善图像 inpainting. 这种方法为处理无效像素提供了更灵活和更适应的方法,提高了视觉质量.

    科学领域:

    • 计算机视觉 计算机视觉
    • 深度学习 (Deep Learning) 是一种深度学习.
    • 图像处理 图像处理

    背景情况:

    • 图像绘制中的标准卷积方法会导致颜色差异和模糊性.
    • 部分卷积 (PConv) 通过使用硬面具部分解决了这一问题,但缺乏像素有效度度表示和有效的信息共享.

    研究的目的:

    • 提出一种新的面具引导卷积 (MagConv) 方法,以实现更优质的图像绘制.
    • 为了提高数据利用效率,并改善在inpainting过程中处理无效像素.

    主要方法:

    • MagConv使用图像和掩码路径之间的共享卷积内核进行联合优化.
    • 一个可学习的分片激活函数取代了PConv的反向函数,为无效像素提供可适应的补偿.
    • MagConv生成一个软面罩,表示像素有效性,并将卷积内核分为正和负权重,以进行准确的评估.

    主要成果:

    • 在图像绘制任务中,MagConv实现了良好的视觉质量.
    • 对CelebA,Paris StreetView和Places2数据集的实验表明,与最先进的方法相比,它们的性能优越.
    • 该方法有效地处理不同程度的像素有效性,导致更准确的 inpainting.

    更多相关视频

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    2.8K
    Quantifying Microglia Morphology from Photomicrographs of Immunohistochemistry Prepared Tissue Using ImageJ
    08:44

    Quantifying Microglia Morphology from Photomicrographs of Immunohistochemistry Prepared Tissue Using ImageJ

    Published on: June 5, 2018

    68.2K

    相关实验视频

    Last Updated: Jul 21, 2025

    Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction
    06:19

    Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

    Published on: August 16, 2024

    449
    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    2.8K
    Quantifying Microglia Morphology from Photomicrographs of Immunohistochemistry Prepared Tissue Using ImageJ
    08:44

    Quantifying Microglia Morphology from Photomicrographs of Immunohistochemistry Prepared Tissue Using ImageJ

    Published on: June 5, 2018

    68.2K

    结论:

    • MagConv在图像绘制中提供了显著的进步,通过使图像和面具信息之间的有效交互成为可能.
    • 拟议的技术为损坏的像素提供了更灵活,更准确的补偿,从而提高了恢复质量.