Summary

In the rapidly evolving realm of technology, computer vision has transformed from mere image recognition into an integral component of countless real-world applications. As these applications span diverse fields such as autonomous vehicles and medical diagnostics, the pressure on computer vision models to deliver accurate and reliable predictions intensifies. With the growing sophistication of these models comes a dire need: quantifying prediction uncertainties.

This is where conformal prediction shines. Unlike traditional models that typically output a singular prediction, conformal prediction offers a range of potential outcomes, each coupled with a confidence measure. This novel approach grants users a detailed perspective on model predictions, which is invaluable for applications where precision is paramount.

This chapter delved into the symbiotic relationship between conformal prediction and computer vision. We started by emphasizing the importance of uncertainty...