On APEER we decided to implement partial annotation because we are used to microscopy datasets with a large number of objects per image. In such cases it's just not efficient to annotate all objects of a single image for ML training. It's rather more beneficial to include some objects from different images, which span multiple experiments. This approach allows to include objects of all sizes, shapes and colors which you expect to segment. Such a dataset allows us to train a much more robust segmentation model.