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相关概念视频

Force Classification01:22

Force Classification

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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,...
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Plotting and Calibrating the Root Locus01:19

Plotting and Calibrating the Root Locus

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Root loci often diverge as system poles shift from the real axis to the complex plane. Key points in this transition are the breakaway and break-in points, indicating where the root locus leaves and reenters the real axis. The branches of the root locus form an angle of 180/n degrees with the real axis, where n is the number of branches at a breakaway or break-in point.
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is...
107
Structural Classification of Joints01:20

Structural Classification of Joints

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Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
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Functional Classification of Joints01:09

Functional Classification of Joints

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Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
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Root Mean Square00:57

Root Mean Square

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If in an experiment, data values have a probability of being both positive and negative, neither the arithmetic mean, the geometric mean, nor the harmonic mean can be used to calculate the central tendency of the data set. In particular, if the positive and negative values are equally likely, the arithmetic mean is close to zero.
For example, consider the velocity of gas molecules in a container. The gas molecules are moving in different directions, which might impart positive and negative...
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Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
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相关实验视频

Updated: Jun 18, 2025

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
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一种基于YOLOv5s的白菜根姿势识别方法.

Fen Qiu1, Chaofan Shao2, Cheng Zhou2

  • 1Huzhou Academy of Agricultural Sciences, Huzhou, 313000, Zhejiang, China.

Heliyon
|July 29, 2024
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概括
此摘要是机器生成的。

这项研究提出了一种新的方法来识别白菜根的姿势,它结合了深度学习和图像处理. 该技术精确检测根的倾斜,提高机械收获效率,减少作物损害.

关键词:
000000 这样就好了.第1111章 这是一件好事卷心菜的根 卷心菜的根倾向的识别 倾向的识别机器视觉 机器视觉 机器视觉对象检测检测对象检测对象检测

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RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols
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科学领域:

  • 农业工程 农业工程
  • 计算机视觉 计算机视觉
  • 机器人技术 机器人技术 机器人技术

背景情况:

  • 有效,非破坏性的收获对于保持白菜质量至关重要.
  • 目前的机械收获缺乏根姿势识别,影响切割准确度.
  • 外部叶子的根堵塞使准确的角度检测变得复杂.

研究的目的:

  • 开发一个精确的白菜根姿势识别系统.
  • 为了提高机械收获中根切割的精度.
  • 为了降低自动卷心菜收获过程中的损害率.

主要方法:

  • 利用YOLOv5的深度学习来进行初始的ROI检测.
  • 应用了传统的图像处理,格雷厄姆算法,以及最小环形矩形来计算根倾角.
  • 开发了一种混合方法,将深度学习与经典图像分析结合起来.

主要成果:

  • 在根姿势识别方面实现了高精度 (98.7%) 和回忆 (98.6%).
  • 在角度检测中显示出低平均绝对误差 (0.80°) 和相对误差 (1.34%).
  • 在角测量中成功解决了叶子封闭所带来的挑战.

结论:

  • 拟议的方法准确地确定了白菜根的倾斜度,即使有叶子封闭.
  • 将该系统集成到机械收割机中可以显著减少卷心菜的损坏.
  • 这一进步有助于更高效和质量维护的自动收获.