Problem
Scenario
You are training an image model and notice that the data contains noise, such as blur, compression artifacts, sensor noise, and occasional mislabeled examples. You want the model to generalize well instead of learning spurious patterns from corrupted inputs.
Question
How would you handle noise in image data?
You are practicing as a guest. Sign up free to get your answer graded with AI feedback. Your draft stays right here.
