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相关概念视频

Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

298
Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
298
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

331
A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
331
Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

341
A stroke engine has a slider-crank mechanism that converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider.
When an external force is exerted, it sets the crank into a rotational movement. This, in turn, instigates the motion of the connecting rod, leading to what is referred to as a general plane motion. This process involves two key points - point A on the connecting rod...
341
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

215
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
215
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

389
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
389
Rolling Resistance01:21

Rolling Resistance

274
When a solid cylinder rolls steadily on a rigid surface, the normal force applied by the surface on the cylinder is perpendicular to the tangent at the contact point. However, since no materials are entirely rigid, the surface's reaction to the cylinder involves a range of normal pressures.
For instance, imagine a hard cylinder rolling on a comparatively soft surface. The cylinder's weight compresses the surface beneath it. As the cylinder moves, the material in front of it slows down...
274

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相关实验视频

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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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基于Mamba_ViT的轻量级车辆检测

Ze Song1, Yuhai Wang1, Shuobo Xu1

  • 1School of Information and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China.

Sensors (Basel, Switzerland)
|November 27, 2024
PubMed
概括

这项研究介绍了Mamba_ViT_YOLO,一种新的车辆检测算法. 它增强了特征提取和融合,提高了智能交通系统的准确性和效率.

科学领域:

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

背景情况:

  • 车辆检测对于智能交通管理和自动驾驶至关重要.
  • 目前使用卷积神经网络 (CNN) 的深度学习方法在完全捕捉复杂的交通场景方面存在局限性.
  • 依赖单一特征提取单元阻碍了全面的车辆信息理解.

研究的目的:

  • 开发一个轻量级和有效的车辆检测算法.
  • 在现实交通场景中提高车辆检测的准确性和效率.
  • 解决当前深度学习模型中单个特征提取的局限性.

主要方法:

  • 提出了一种新的特征提取架构,Mamba_ViT,它独立处理浅层和深层特征,以获得更丰富的上下文表示.
  • 引入了多级特征融合机制,以有效地整合多种特征.
  • 通过将Mamba_ViT架构与YOLO框架结合起来,开发了Mamba_ViT_YOLO算法.

主要成果:

  • 在UA-DETRAC数据集上,Mamba_ViT_YOLO算法表现出更好的性能.
  • 与YOLOv8算法相比,mAP@50实现了3.2%的增加.
  • 与YOLOv8相比,拟议的模型仅使用了60%的参数,这表明效率提高.
关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.轻量级的轻量级的轻量级的轻量级的对象检测检测对象检测对象检测车辆检测 车辆检测 车辆检测

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结论:

  • Mamba_ViT_YOLO算法在车辆检测方面取得了重大进展.
  • 新的Mamba_ViT架构和特征融合机制有助于更全面的特征提取.
  • 这种轻量级模型为实时智能交通管理和自动驾驶系统提供了有前途的解决方案.