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.
Overview
Syllabus
- Introduction
- What is computer vision?
- How does a computer start to "see?"
- What some of the different types of computer vision problems?
- How can someone start tackling a computer vision problem? Includes collecting, labeling, organizing, pre-processing data.
- What is image augmentation?
- What does it mean to build a computer vision model?
- Why does this process have so many steps?
- Acknowledging ethics and equity in computer vision
Taught by
Roboflow
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