You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello
I’m preparing a dataset for a Mask R-CNN model, involving images of cats and smaller, distinct spots on these cats. While the dataset has more instances of “spots” than “cats,” the latter covers a much larger area in the images. I’m concerned this might bias the model toward the “cat” class due to its larger pixel coverage.
My question is:
Could this difference in area coverage introduce significant training bias towards the “cat” class?
Any advice or resources would be appreciated.
The text was updated successfully, but these errors were encountered:
Hello
I’m preparing a dataset for a Mask R-CNN model, involving images of cats and smaller, distinct spots on these cats. While the dataset has more instances of “spots” than “cats,” the latter covers a much larger area in the images. I’m concerned this might bias the model toward the “cat” class due to its larger pixel coverage.
My question is:
Could this difference in area coverage introduce significant training bias towards the “cat” class?
Any advice or resources would be appreciated.
The text was updated successfully, but these errors were encountered: