Jove
Visualize
联系我们

相关概念视频

Force Classification01:22

Force Classification

1.3K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.3K
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.6K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.6K
Survival Tree01:19

Survival Tree

110
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
110

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 adversarial example attack method based on predicted bounding box adaptive deformation in optical remote sensing images.

PeerJ. Computer science·2024
Same author

Design and Control of a 1-DOF MRI Compatible Pneumatically Actuated Robot with Long Transmission Lines.

IEEE/ASME transactions on mechatronics : a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division·2011
Same author

Effect of oxidized low-density lipoprotein concentration polarization on human smooth muscle cells' proliferation, cycle, apoptosis and oxidized low-density lipoprotein uptake.

Journal of the Royal Society, Interface·2011
Same author

Acrolein hydrogenation on Pt(211) and Au(211) surfaces: a density functional theory study.

Physical chemistry chemical physics : PCCP·2011
Same author

Anhydrous proton-conducting membrane based on poly-2-vinylpyridinium dihydrogenphosphate for electrochemical applications.

The journal of physical chemistry. B·2011
Same author

Pharmacophore identification, virtual screening and biological evaluation of prenylated flavonoids derivatives as PKB/Akt1 inhibitors.

European journal of medicinal chemistry·2011
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: Jul 19, 2025

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

1.9K

图像分类对抗性攻击,改进了大小转换和组合模型.

Chenwei Li1,2, Hengwei Zhang1,2, Bo Yang1,2

  • 1State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, Henan, China.

PeerJ. Computer science
|August 7, 2023
PubMed
概括

这项研究增强了使用模型增强和组合模型的黑子攻击中的对抗性示例可转移性. 拟议的调整大小的不变性方法提高了对各种模型的对抗性攻击成功率.

关键词:
对抗性的例子.计算机图形 计算机图形卷积神经网络是一种卷积神经网络.组合模型组合模型图像的分类图像的分类.图像转换 图像转换 图像转换改进了大小调整的功能.可转让性 可转让性

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

570
Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

1.6K

相关实验视频

Last Updated: Jul 19, 2025

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

1.9K
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

570
Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

1.6K

科学领域:

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

背景情况:

  • 卷积神经网络 (CNN) 在计算机视觉方面很强大,但对对抗性示例很脆弱.
  • 敌对的例子,不可察觉的输入扰动,突出显示CNN漏洞,并用于评估网络稳定性.
  • 与白盒攻击相比,黑盒攻击的成功率较低,可转移性有限.

研究的目的:

  • 为了提高黑子攻击中对抗性示例的成功率和可转移性.
  • 引入一种新的模型增强技术,用于生成更强大的对抗性示例.
  • 加强神经网络对复杂的对抗性攻击的安全评估.

主要方法:

  • 提出了一个调整尺寸的不变性方法用于模型增强,灵感来自数据增强技术.
  • 利用改进的调整尺寸转换来增强模型增强功能.
  • 采用集体模型来生成具有更高可转移性的对抗性示例.

主要成果:

  • 拟议的调整大小的不变性方法与基线方法相比显示出更高的性能.
  • 在正常和防御模型中,在黑子攻击成功率方面取得了显著的改进.
  • 验证了集合模型在生成更多可转移的对抗性示例方面的有效性.

结论:

  • 调整尺寸的不变性方法是模型增强在对抗性攻击的背景下有效的方法.
  • 提出的技术增强了对抗性示例的可转移性,对模型安全构成更大的挑战.
  • 这项研究有助于更好地理解和评估神经网络对抗对抗干扰的稳定性.