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O'Neil, Gina L., Goodall, Jonathan L., Behl, Madhur, Saby, Linnea (2020) Deep learning Using Physically-Informed Input Data for Wetland Identification. Environmental Modelling & Software, 126. 104665pp. doi:10.1016/j.envsoft.2020.104665

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Reference TypeJournal (article/letter/editorial)
TitleDeep learning Using Physically-Informed Input Data for Wetland Identification
JournalEnvironmental Modelling & Software
AuthorsO'Neil, Gina L.Author
Goodall, Jonathan L.Author
Behl, MadhurAuthor
Saby, LinneaAuthor
Year2020 (April)Volume126
PublisherElsevier BV
DOIdoi:10.1016/j.envsoft.2020.104665Search in ResearchGate
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Mindat Ref. ID9715596Long-form Identifiermindat:1:5:9715596:0
GUID0
Full ReferenceO'Neil, Gina L., Goodall, Jonathan L., Behl, Madhur, Saby, Linnea (2020) Deep learning Using Physically-Informed Input Data for Wetland Identification. Environmental Modelling & Software, 126. 104665pp. doi:10.1016/j.envsoft.2020.104665
Plain TextO'Neil, Gina L., Goodall, Jonathan L., Behl, Madhur, Saby, Linnea (2020) Deep learning Using Physically-Informed Input Data for Wetland Identification. Environmental Modelling & Software, 126. 104665pp. doi:10.1016/j.envsoft.2020.104665
In(n.d.) Environmental Modelling & Software Vol. 126. Elsevier BV

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O'Neil, Gina L., Saby, Linnea, Band, Lawrence E., Goodall, Jonathan L. (2019) Effects of LiDAR DEM Smoothing and Conditioning Techniques on a Topography‐Based Wetland Identification Model. Water Resources Research, 55 (5) 4343-4363 doi:10.1029/2019wr024784
Sadler, Jeffrey M., Goodall, Jonathan L., Behl, Madhur, Morsy, Mohamed M., Culver, Teresa B., Bowes, Benjamin D. (2019) Leveraging open source software and parallel computing for model predictive control of urban drainage systems using EPA-SWMM5. Environmental Modelling & Software, 120. 104484pp. doi:10.1016/j.envsoft.2019.07.009
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Castronova, Anthony M., Goodall, Jonathan L. (2013) Simulating watersheds using loosely integrated model components: Evaluation of computational scaling using OpenMI. Environmental Modelling & Software, 39. 304-313 doi:10.1016/j.envsoft.2012.01.020
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