Jove
Visualize
联系我们

相关概念视频

Machines01:19

Machines

250
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
250
Machines: Problem Solving II01:30

Machines: Problem Solving II

296
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
296
Machines: Problem Solving I01:22

Machines: Problem Solving I

300
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
300
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

97
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
97
Mechanical Efficiency of Real Machines01:14

Mechanical Efficiency of Real Machines

639
The mechanical efficiency of a machine is a fundamental concept that describes how effectively a machine can convert input work into output work. According to this concept, the efficiency of a machine is equal to the ratio of the output work to the input work. An ideal machine, meaning a machine that has no energy losses, has an efficiency of one. This implies that the input work and the output work are equal.
However, in reality, no machine can be truly ideal, and all of them experience some...
639
Upsampling01:22

Upsampling

204
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
204

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Toward leveraging intrinsic point cloud features in 3D adversarial attacks.

PloS one·2026
Same author

Rate-Distortion Theory in Coding for Machines and Its Applications.

IEEE transactions on pattern analysis and machine intelligence·2025
Same author

Efficient Signed Graph Sampling via Balancing & Gershgorin Disc Perfect Alignment.

IEEE transactions on pattern analysis and machine intelligence·2025
Same author

Privacy-Preserving Autoencoder for Collaborative Object Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2024
Same author

Point Cloud Video Super-Resolution via Partial Point Coupling and Graph Smoothness.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2022
Same author

Scalable Image Coding for Humans and Machines.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2022
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jun 7, 2025

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.6K

学习了人类和机器的可扩展视频编码.

Hadi Hadizadeh1, Ivan V Bajić1

  • 1School of Engineering Science, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6 Canada.

EURASIP journal on image and video processing
|November 18, 2024
PubMed
概括
此摘要是机器生成的。

一种新的视频编码方法支持机器视觉任务和人类观看. 这种端到端学习的编解码器为机器分析和人类审查提供了高效的视频压缩,性能优于现有的方法.

关键词:
对机器进行编码.深度学习是一种深度学习.可扩展的编码.视频分析 视频分析视频压缩方法 视频压缩

更多相关视频

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

8.9K
Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth
13:11

Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth

Published on: May 20, 2010

12.7K

相关实验视频

Last Updated: Jun 7, 2025

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.6K
Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

8.9K
Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth
13:11

Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth

Published on: May 20, 2010

12.7K

科学领域:

  • 计算机视觉和机器学习
  • 视频压缩和信号处理

背景情况:

  • 传统的视频编码专注于人类观看,但深度神经网络 (DNN) 能够实现机器视觉应用.
  • 现有的视频编解码器没有被优化为机器分析和人类审查中的双重使用,需要一种新的方法.
  • 像交通监控这样的应用需要连续的机器分析,偶尔有人类监督.

研究的目的:

  • 引入一个端到端可学习的视频编解码器,旨在用于机器视觉和人类观看.
  • 为了实现高效,可扩展的视频表示和压缩,用于双重用途的应用.
  • 提高视频分析性能,同时保持人类感知质量.

主要方法:

  • 开发了一个端到端可学习的视频编解码器,用于机器视觉任务的基础层.
  • 整合了一个增强层,用于人类观看重建,利用条件编码原则.
  • 在四个标准视频数据集上对框架进行了评估.

主要成果:

  • 拟议的编解码器的基本层在机器视觉任务中显著超过了最先进的学习和传统编解码器.
  • 增强层与基础层相结合,实现了与现有的人类查看编解码器可比的性能.
  • 条件编码原理有助于增强压缩收益.

结论:

  • 开发的可学习视频编解码器有效地支持机器视觉任务和人类以可扩展的方式观看.
  • 这种双重用途的编解码器对于需要自动化分析和人类审查的应用程序来说是一个重大进步.
  • 该框架展示了机器视觉的卓越效率,同时保持了人类感知的质量.