C. De Vleeschouwer

This paper develops a method to train deep-learning models for multi-species canopy segmentation using FCNNs and pseudo-labeling, achieving high accuracy with reduced human effort.

The paper introduces a cell segmentation framework using random ferns and graph-cuts to extract cell boundaries from live imaging data, validated on a manually annotated dataset.