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

Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

6.7K
Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
6.7K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

128
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
128
Fusion of Secretory Vesicles with the Plasma Membrane01:26

Fusion of Secretory Vesicles with the Plasma Membrane

11.1K
Proteins and neurotransmitters in secretory vesicles can be released from a cell upon vesicle docking, priming, and fusion with the plasma membrane. Vesicles are docked and primed in preparation for the quick exocytosis of their contents in response to a stimulus. The fusion process is mainly carried out by a SNAP Receptor or SNARE complex, consisting of synaptobrevin, syntaxin-1, and SNAP-25.
In 1993, Jim Rothman proposed that the antiparallel pairing of vesicular and transmembrane SNAREs, or...
11.1K
Deconvolution01:20

Deconvolution

186
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...
186
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

5.5K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
5.5K
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

482
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...
482

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

An ensemble machine learning model based on magnetic resonance imaging features for diagnosing deep infiltrating endometriosis.

Frontiers in physiology·2026
Same author

Comparative analysis of microplastic and microbial communities in varied aquatic environments: Disparities in occurrence, interconnections, and ecological implications.

Journal of hazardous materials·2025
Same author

The NET-DNA-CCDC25 inhibitor di-Pal-MTO suppresses tumor progression and promotes the innate immune response.

Cellular & molecular immunology·2025
Same author

Effect of Nitrogen on Microbial Communities of Purple Mudstone Weathering Products in Southwest China: A Column Experiment.

Microorganisms·2024
Same author

Learning Student Network Under Universal Label Noise.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2024
Same author

Global trends and research hotspots of PCSK9 and cardiovascular disease: a bibliometric and visual analysis.

Frontiers in cardiovascular medicine·2024
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
查看所有相关文章

相关实验视频

Updated: Jul 17, 2025

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.2K

基于多层融合特征的知识蒸.

Shengyuan Tan1, Rongzuo Guo1, Jialiang Tang2

  • 1College of Computer Science, Sichuan Normal Univeersity, Chengdu, Sichuan, 610101, China.

PloS one
|August 28, 2023
PubMed
概括
此摘要是机器生成的。

多功能融合知识蒸 (MFKD) 通过融合来自多个教师网络层的功能来增强学生网络. 这种方法显著提高了图像分类任务的性能.

更多相关视频

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

568

相关实验视频

Last Updated: Jul 17, 2025

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.2K
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

568

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 知识蒸培养较小的学生网络,使用来自较大,预先训练有素的教师网络的知识.
  • 当前的方法往往使用来自有限的教师网络层的简单特征,忽视了更丰富,融合的信息.

研究的目的:

  • 建议多功能融合知识蒸 (MFKD) 改进知识传输.
  • 为了利用来自不同教师网络层的表达性,融合特征.

主要方法:

  • 从教师网络的多个网络层 (前面,中间,底部) 提取特征地图.
  • 设计一个多功能融合方案,以整合这些多样化的功能.
  • 培训学生网络使用丰富的,融合的功能.

主要成果:

  • 融合特征地图包含的信息比单个位置的特征更有意义.
  • 在CIFAR-100上,MFKD提高了ResNet20的Top-1精度1.82%,VGG8的Top-1精度提高了3.35%.
  • 超过了几种最先进的知识蒸方法.

结论:

  • MFKD使学生网络能够从更丰富,融合的知识中有效地学习.
  • 拟议的方法提供了一种优越的知识蒸方法,以提高模型性能.