Lee, Hyunho, and Li, Wenwen. Improving interpretability of deep active learning for flood inundation mapping through class ambiguity indices using multi-spectral satellite imagery. Retrieved from https://par.nsf.gov/biblio/10574188. Remote Sensing of Environment 309.C Web. doi:10.1016/j.rse.2024.114213.

Lee, Hyunho, & Li, Wenwen. Improving interpretability of deep active learning for flood inundation mapping through class ambiguity indices using multi-spectral satellite imagery. Remote Sensing of Environment, 309 (C). Retrieved from https://par.nsf.gov/biblio/10574188. https://doi.org/10.1016/j.rse.2024.114213

Lee, Hyunho, and Li, Wenwen. "Improving interpretability of deep active learning for flood inundation mapping through class ambiguity indices using multi-spectral satellite imagery". Remote Sensing of Environment 309 (C). Country unknown/Code not available: Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2024.114213. https://par.nsf.gov/biblio/10574188.

@article{osti_10574188,
place = {Country unknown/Code not available}, title = {Improving interpretability of deep active learning for flood inundation mapping through class ambiguity indices using multi-spectral satellite imagery}, url = {https://par.nsf.gov/biblio/10574188}, DOI = {10.1016/j.rse.2024.114213}, abstractNote = {}, journal = {Remote Sensing of Environment}, volume = {309}, number = {C}, publisher = {Remote Sensing of Environment}, author = {Lee, Hyunho and Li, Wenwen}, }