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

Deconvolution01:20

Deconvolution

532
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...
532
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

1.1K
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
1.1K
Fischer Projections02:18

Fischer Projections

16.1K
Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines. While...
16.1K
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

12.1K
Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
12.1K
Data Collection by Survey01:07

Data Collection by Survey

8.5K
The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
8.5K
Stratified Sampling Method01:16

Stratified Sampling Method

14.4K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
14.4K

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

Caregiving burden and depressive symptoms among rural caregivers of older adults living with disabilities in China: the role of formal and informal support.

Global health action·2026
Same author

Comparing the roles of f0, speech rate, and timbre in expressing and perceiving politeness in Mandarin speech.

Phonetica·2026
Same author

Phosphoethanolamine cytidylyltransferase 2 integrates DAG metabolism and TBK1 activation to regulate antiviral innate immunity.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Cryo-EM Structure of the TRPC1/5 Heteromer Enables Design of Antidepressant and Anxiolytic Drug with Reduced Side Effects.

Nature communications·2026
Same author

Impact of Attachment on Emotional Experience and Expression: A Physiological and Acoustic Investigation.

Journal of speech, language, and hearing research : JSLHR·2026
Same author

Accelerated Proton Transfer Channel for Breaking the Bottlenecks of Activity and Stability at Industrial-Scale Anion Exchange Membrane Water Electrolysis.

Angewandte Chemie (International ed. in English)·2026
Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

IEEE transactions on neural networks and learning systems·2026
Same journal

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

IEEE transactions on neural networks and learning systems·2026
Same journal

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

IEEE transactions on neural networks and learning systems·2026
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
查看所有相关文章

相关实验视频

Updated: Jan 10, 2026

Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation
16:23

Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation

Published on: May 23, 2017

11.7K

深度模型融合:一项调查

Weishi Li, Yong Peng, Miao Zhang

    IEEE transactions on neural networks and learning systems
    |November 25, 2025
    PubMed
    概括
    此摘要是机器生成的。

    深度模型融合结合了多个深度学习 (DL) 模型以提高性能. 本调查对重量平均,模式连接,对齐和集体学习等融合方法进行了分类,解决了大规模模型中的挑战.

    更多相关视频

    Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
    13:01

    Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

    Published on: April 10, 2016

    34.6K
    Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
    09:19

    Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

    Published on: April 18, 2025

    1.4K

    相关实验视频

    Last Updated: Jan 10, 2026

    Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation
    16:23

    Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation

    Published on: May 23, 2017

    11.7K
    Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
    13:01

    Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

    Published on: April 10, 2016

    34.6K
    Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
    09:19

    Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

    Published on: April 18, 2025

    1.4K

    科学领域:

    • 人工智能的人工智能
    • 机器学习 机器学习
    • 深度学习 (Deep Learning) 是一种深度学习.

    背景情况:

    • 深度模型融合集成了多个深度学习 (DL) 模型,通过结合它们的优势和减轻单个模型的弱点来提高性能.
    • 深度模型融合存在挑战,特别是对于大型模型,如大型语言模型 (LLM) 和基础模型,由于高计算成本和模型异质性.

    研究的目的:

    • 为深度模型融合技术的最新进展提供全面的调查.
    • 分类和分析现有的模型融合方法,并确定未来的研究方向.

    主要方法:

    • 深度模型融合方法分为四种主要类型:重量平均 (WA),模式连接,对齐和集体学习.
    • 重量平均:将模型参数合并,通过平均它们来近似最佳解决方案.
    • 模式连接:在不增加损失的路径上转换模型,以实现一致的功能和更好的融合.
    • 调整:在合并之前在模型之间匹配相应的单位,以利用模型间的关系.
    • 集合学习:在推断过程中结合多个模型的预测,以提高准确性和稳定性.

    主要成果:

    • 现有的深度模型融合技术可以广泛分为参数级融合 (WA,模式连接,对齐) 和推断级融合 (集体学习).
    • 每种方法都为整合多种深度学习模型提供了独特的优势.

    结论:

    • 深度模型融合是提高DL模型性能的一种有前途的技术,特别是在大型架构中.
    • 解决诸如计算成本和模型干扰等挑战对于推进该领域至关重要.
    • 未来的研究应该探索新的融合策略和异质和大规模模型的优化技术.