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相关概念视频

Hierarchy of Motor Control01:18

Hierarchy of Motor Control

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The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
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End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
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Aggregates Classification01:29

Aggregates Classification

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Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
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Fixation and Sectioning01:03

Fixation and Sectioning

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Two basic types of preparation are used to visualize specimens with a light microscope: wet mounts and fixed specimens.
The simplest type of preparation is the wet mount, in which the specimen is placed in a drop of liquid on the slide. A liquid specimen can be directly deposited on the slide using a dropper. Solid specimens, such as skin scraping, can be placed on the slide before adding a drop of liquid to prepare the wet mount. Sometimes the liquid is simply water, but stains are often added...
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Design Example: Aggregate Gradation01:24

Design Example: Aggregate Gradation

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The right type and quality of aggregates are crucial for concrete as they significantly influence its properties, mix proportions, and cost-effectiveness. If different sources are available for sand, the commonly used fine aggregate in concrete, the selection of sand is primarily based on its gradation.
The grading, or particle-size distribution, of sand is determined using sieve analysis, with standard sizes ranging from 150 μm to 10 mm (ASTM No. 100 sieve to 3⁄8 in. sieve). Sand is...
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
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统一的粒度控制器用于交互式细分的交互式细分.

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    此摘要是机器生成的。

    本研究引入了一种新的可控制细粒度的交互式分割 (IS) 范式,UniGraCo,以精确控制细分化的细节. UniGraCo克服了模糊性和冗余性,为用户提供了一个更有效,更实用的交互工具.

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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
    • 图像分析 图像分析

    背景情况:

    • 交互式细分 (IS) 从对象细分的稀疏提示中推断出人类的意图.
    • 稀疏到密集映射中的模糊性导致用户的试错和次优细分细分度.
    • 现有的多细分化IS方法缺乏可扩展性,并产生冗余的输出.

    研究的目的:

    • 开发一个可控制细粒度的IS范式,解决模两可,并允许用户精确控制细分化的细节.
    • 引入一个统一的粒度控制器 (UniGraCo),支持各种控制信号,以满足各种细分需求.
    • 在交互式细分任务中提高系统效率和实用性.

    主要方法:

    • 提出了一种统一的颗粒度控制器 (UniGraCo),具有多种类型的可选控制信号,用于灵活调节颗粒度.
    • 开发了一种自动化数据引擎,用于低成本生成高质量,多颗粒度的面具控制信号数据对.
    • 设计了一个可控制细粒度的学习策略,以高效稳定地训练IS模型,保持细分能力.

    主要成果:

    • 在复杂的实例和部分级别细分场景中,UniGraCo在现有方法上表现出显著的优势.
    • 自动化数据引擎有效降低了注释成本,同时产生了丰富的培训数据.
    • 可控制细分度的学习策略成功地赋予了预先训练的IS模型对细分细分度的精确控制.

    结论:

    • UniGraCo提供了一种创意和有效的解决方案,用于在交互式细分中精确控制颗粒度.
    • 拟议的范式在效率和实用性方面显著改进了现有的多颗粒度IS方法.
    • UniGraCo显示出强大的潜力,作为复杂的细分任务的实用交互工具.