juniorComputer Vision
What are precision and recall in Computer Vision?
Updated May 15, 2026
Short answer
Precision measures correctness of positive predictions; recall measures coverage of actual positives.
Deep explanation
Precision = TP/(TP+FP), Recall = TP/(TP+FN). They balance false positives and false negatives.
Real-world example
Used in face detection systems to evaluate accuracy.
Common mistakes
- Confusing precision with accuracy.
Follow-up questions
- What is F1 score?
- When is recall more important?