Title
Semantic segmentation with labeling uncertainty and class imbalance applied to vegetation mapping
Abstract
•We propose a loss function for semantic segmentation methods in vegetation.•We address class imbalance and labeling uncertainty.•Results using the proposed method proved superior to traditional approaches.
Year
DOI
Venue
2022
10.1016/j.jag.2022.102690
International Journal of Applied Earth Observation and Geoinformation
Keywords
DocType
Volume
Semantic segmentation,Labeling uncertainty,Class weighting,Loss function
Journal
108
ISSN
Citations 
PageRank 
1569-8432
0
0.34
References 
Authors
0
15