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相关概念视频

Methods of Classification and Identification01:28

Methods of Classification and Identification

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Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
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Machines: Problem Solving II01:30

Machines: Problem Solving II

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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.
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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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Machines: Problem Solving I01:22

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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...
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对于产品代码识别的机器视觉方法的最新进展:系统审查

Jarmo Koponen1, Keijo Haataja1, Pekka Toivanen1

  • 1School of Computing, Kuopio campus, University of Eastern Finland, Kuopio, Pohjois-Savo, FI-70211, Finland.

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概括

对于产品文本识别的机器视觉有了显著的进步,深度学习神经网络 (DNN) 现在克服了阅读包装上的制造标记的常见挑战. 这种进化改善了制药和食品产品的处理.

科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 模式识别 模式识别

背景情况:

  • 制造标记对于处理药品和易腐食品至关重要.
  • 目前的方法包括光学字符识别 (OCR) 和神经网络.
  • 识别这些文本在现实世界的应用中带来了重大挑战.

研究的目的:

  • 在8年的时间里 (2012-2020年) 系统地审查产品文本识别的机器视觉方法的演变.
  • 确定在产品表面识别文本时遇到的常见挑战.
  • 评估识别技术的性能和发展.

主要方法:

  • 对2012年至2020年间发表的文章进行系统的文献综述.
  • 搜索的数据库:科学直接/SCOPUS和谷歌学者.
  • 包括详细介绍识别方法,性能,成像,产品类型和文本的研究.

主要成果:

  • 产品文本识别方法取得了重大进展,特别是在审查期间的最后两年.
  • 深度学习神经网络 (DNN) 架构,像卷积神经网络 (CNN),擅长从包装图像中提取特征.
  • 最近的方法采用双网络方法来检测文本区域和字符识别,解决常见的困难.
关键词:
字符识别 字符识别深度学习 (Deep Learning) 是一种深度学习.图像系统的成像系统机器视觉 机器视觉 机器视觉制造业 制造业 制造业 制造业在OCR中,OCR是OCR.包装 包装是一种包装.产品 产品 产品 产品 产品

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结论:

  • 有限的研究符合审查标准,重点是用于制造品牌识别的机器视觉.
  • 方法从OCR演变为先进的深度学习方法.
  • 深度学习能够实现强大的文本识别,尽管常见的行业挑战.