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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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可变形的动态采样和动态可预测的面具采矿用于图像绘制.

Cai Cai, Yu Zeng, Shu Yang

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    此摘要是机器生成的。

    这项研究引入了一种新的可变形动态采样 (DDS) 机制用于图像绘制,通过智能采样图像区域来显著减少文物. 该方法通过在训练期间考虑区域可预测性来提高图像恢复质量.

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    科学领域:

    • 计算机视觉 计算机视觉
    • 人工智能的人工智能
    • 图像处理 图像处理

    背景情况:

    • 现有的图像 inpainting 方法使用标准的卷积层,通过对所有图像区域进行均处理,从而产生工件.
    • 这些方法在推断过程中无法区分缺失区域和有效区域,并且在培训过程中不考虑区域可预测性.

    研究的目的:

    • 开发一种先进的图像绘制技术,克服当前方法的局限性.
    • 为了减少文物和提高恢复图像的质量.

    主要方法:

    • 提出一种基于可变形卷曲 (DC) 的可变形动态采样 (DDS) 机制.
    • 引入一个约束,以防止腐败地区内的抽样.
    • 实施内容意识的动态内核选择 (DKS) 对DCs.
    • 用动态生成的孔口罩训练涂装模型,优先考虑可预测的区域.

    主要成果:

    • 拟议的DDS机制与DKS有效地减少了图像中的工件.
    • 使用动态开采可预测区域进行训练,提高了该模型恢复大缺失区域的能力.
    • 实验结果显示,与最先进的油漆方法相比,性能优越.

    结论:

    • 开发的图像绘制方法显著提高了修复质量.
    • DDS机制和动态面具生成提供了更强大的方法来处理缺失的图像数据.