I’m working on a semantic segmentation task in point clouds, I have 9 classes, labeled from 0 to 8. when 0 is unlabeled points.
The classes are widely varied with the number of points, vegetation and ground are around 70% of the point cloud, and fence and light poles account for very few points. I understand that this affects the training process, so we should initialize the weights with respect to the proportion of the classes.
I’d like to have more explanation regarding this topic.
Thanks very much.