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1
- Introduction
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- What is computer vision?
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- How does a computer start to "see?"
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- What some of the different types of computer vision problems?
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- How can someone start tackling a computer vision problem? Includes collecting, labeling, organizing, pre-processing data.
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- What is image augmentation?
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- What does it mean to build a computer vision model?
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- Why does this process have so many steps?
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- Acknowledging ethics and equity in computer vision
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the fundamentals of computer vision in this 45-minute fireside chat video. Delve into the core concepts of how computers perceive visual information, learn about various types of computer vision problems, and understand the step-by-step process of tackling these challenges. Discover essential techniques such as data collection, labeling, organization, and pre-processing, along with the importance of image augmentation in model training. Gain insights into building computer vision models and the rationale behind the multi-step approach. Conclude with a critical discussion on the ethical considerations and equity issues in the field of computer vision, ensuring a well-rounded understanding of this cutting-edge technology.

Intro to Computer Vision - Fireside

Roboflow
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