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Visual Data Collection for Quality Control

By University of Groningen

Type of course:

Digital learning, Lesson

Language:

EN

Duration:

15 minutes

Proficiency:

Intermediate

Target:

Manager, Professionals, Workers

In the world of quality control and manufacturing, visual data collection is a powerful tool. But how does the camera’s quality impact the accuracy of the data we collect?

This lesson will guide you through the critical relationship between camera quality, including resolution and sensor specifications, and the precision of visual data. You’ll learn how different visual data collection methods, such as real-time video analysis, high-resolution image capture, and advanced 3D scanning, each play a unique role in ensuring high-quality results.

Furthermore, we’ll explore how to match these technologies to specific real-world applications, ensuring that the right tool is used for the right task—whether it’s capturing intricate details of fabric defects or scanning an entire garment for consistency. By the end of the lesson, you’ll have a clearer understanding of how visual data technologies can be applied effectively in manufacturing processes to enhance quality and efficiency.

About The Author

Dilek Dustegor is a Professor of Computing Science at the University of Groningen in the Netherlands. She is interested in bridging the gaps between research, development and implementation using AI and automation. She is pursuing research about modeling, design and analysis of large scale / networked systems using Internet of Things (IoT) and Machine Learning (ML)L techniques, with a special interest in smart city applications. She is a seasoned educator, and loves using the newest educational technologies for an enhanced learning experience.


Learning outcomes

  1. By the end of this lesson, learners will be able to explain the relationship between camera quality (including resolution and sensor specifications) and the accuracy of visual data collection.
  2. By the end of this lesson, learners will be able to describe various methods for collecting and processing visual data, including real-time video analysis, high-resolution image capture, and 3D scanning.
  3. By the end of this lesson, learners will be able to match real-world applications where visual data collection is critical with the appropriate technology for specific tasks.

Topics

Automation and Sensoring, Automation and Robotics, Digital Transformation, Machine Learning

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Content created in 2024
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Course Includes

  • 1 Quiz

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