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相关概念视频

Masking and Demasking Agents01:19

Masking and Demasking Agents

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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...
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Reducing Line Loss01:18

Reducing Line Loss

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In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...
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First Pass Effect01:12

First Pass Effect

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Presystemic elimination, or the first-pass effect, is the metabolism of drugs that reduces their effective concentration at the site of action. Apart from the first-pass effect, the systemic bioavailability of the drug is also reduced by other factors, including incomplete absorption or chemical degradation of drugs.
Depending on the route of administration, drugs can be metabolized in the liver, intestine, lungs, and vasculature. Orally administered drugs are first absorbed through the...
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Vision01:24

Vision

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Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
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Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

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Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
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Depth Perception and Spatial Vision

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Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
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相关实验视频

Updated: Jan 10, 2026

Deep Neural Networks for Image-Based Dietary Assessment
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Deep Neural Networks for Image-Based Dietary Assessment

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FP-ZOO:基于快速补丁的零顺序优化,用于黑盒对视觉模型的对抗性攻击.

Junho Seo1, Seungho Jeon2

  • 1Telecommunications Technology Association, Bundang-ro 47, Bundang-gu, Seongnam-si 13591, Gyeonggi-do, Republic of Korea.

Sensors (Basel, Switzerland)
|November 27, 2025
PubMed
概括
此摘要是机器生成的。

一个新的基于补丁的快速零顺序优化 (FP-ZOO) 攻击增强了深度视觉模型的对抗性强度. FP-ZOO实现了高成功率和更快的生成时间来抵御逃避攻击,改善了模型的安全性.

关键词:
敌对攻击是对抗性的攻击.黑子攻击攻击黑子攻击逃避攻击 逃避攻击视觉模型 视觉模型 视觉模型零度顺序优化优化

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相关实验视频

Last Updated: Jan 10, 2026

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

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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:

  • 深度神经网络 (DNN) 在视觉任务中表现出色,但容易受到对抗性攻击.
  • 逃避攻击,特别是在黑盒设置中,威胁到现实应用中的DNN可靠性.
  • 现有的方法,如零次顺序优化 (ZOO),由于效率低下和内存复杂性,难以处理高分辨率图像.

研究的目的:

  • 提出一种新的基于补丁的快速零顺序优化 (FP-ZOO) 攻击.
  • 为了解决现有的动物园攻击高分辨率图像的局限性.
  • 提高黑盒规避攻击对视觉模型的效率和成功率.

主要方法:

  • FP-ZOO将图像分割成针对性扰动的补丁.
  • 它使用基于概率的采样和epsilon-greedy调度策略来有效地产生干扰.
  • 对CIFAR-10,CIFAR-100和ImageNet数据集进行了大规模的评估.

主要成果:

  • 在非目标攻击中,FP-ZOO在ImageNet上实现了97-100%的攻击成功率.
  • 这次攻击的生成时间比标准的动物园攻击快10秒.
  • 在有针对性的攻击中,FP-ZOO的性能相对较低,这表明了未来研究的领域.

结论:

  • 对于针对视觉模型的非定向回避攻击,FP-ZOO可显著提高效率和有效性.
  • 拟议的方法通过克服先前动物园攻击的局限性,提高了对手的稳定性.
  • 需要进一步的研究来优化FP-ZOO针对目标攻击场景.