I am working on a dataset of 2K images for a semantic segmentation problem. I want to detect and localize small objects, with the smallest mask to be 5x5 pixels. The images include 5 different textures, quite different from each other.
I am using Unet and EfficientNetb0-3 as backbones, but whatever I do, I get underfitting. I've reached the conclusion that it is probably due to the fact that the resolution is too high and the variance as well.
Do you have any advice on how I could overcome this underfitting problem?