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Machine Vision for Quality Control: Introduction and Use Case

By University of Zagreb – FAMENA

Type of course:

Digital learning, Path

Language:

EN

Duration:

1 hour, 40 minutes

Workload:

6 hours

Proficiency:

Intermediate

Target:

Manager, Professionals, Students, Workers

Embark on a dynamic learning journey that introduces you to the core concepts of machine vision, object recognition, and machine vision application in quality control. In this learning path, you’ll look into the basics of machine vision, understand the intricacies of object recognition, and explore how machine vision transforms quality control processes. Engage in activity that involve model training and machine vision system building, and test your knowledge through insightful questions. By the end of this journey, you’ll possess a solid foundation in these transformative technologies and their practical applications, equipping you to make informed contributions in various fields.


Learning outcomes

  1. After completing this learning path, participants are able to identify the principles and techniques of image acquisition and pre-processing in machine vision for quality control.
  2. After completing this learning path, participants are able to define the role of machine learning algorithms in defect detection and classification for quality control in machine vision.
  3. After completing this learning path, participants are able to consider the factors that influence the performance of machine vision systems in quality control.
LessonHow to set up a simple machine vision application for beginners
LessonBasics of Object Recognition and its Industrial Applications
LessonReal-time object classification and counting with Machine Learning for reduced waste

Course Content

LessonMachine Vision for Quality Control - Quiz

Topics

Digital Transformation, Artificial Intelligence (AI)

Provided by

Content created in 2023
+223 enrolled
Take the next step toward your learning goals

Course Includes

  • 2 Quizzes
  • 1 Certificate of achievement

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