@misc{https://doi.org/10.4121/21127528.v3,
  doi = {10.4121/21127528.v3},
  url = {https://data.4tu.nl/articles/dataset/Wetland_Classification_with_Deep_ResU-Net_Convolutional_Neural_Network_and_Multitemporal_Sentinel-1_2_Imagery_and_ALOS_Elevation_Data_A_Case_Study_in_Alberta_Parkland_Grassland_Natural_Region_Canada/21127528/3},
  author = {Onojeghuo, Alex and Onojeghuo, Ajoke Ruth},
  keywords = {Wetlands, Parkland & Grassland Natural Region, Alberta, deep learning, machine learning, ResNet34, CNN, Random Forest, Support Vector Machine, Remote Sensing},
  title = {Wetland Classification with Deep ResU-Net CNN and Multitemporal Sentinel 1 & 2 Imagery and ALOS Elevation Data},
  publisher = {4TU.ResearchData},
  year = {2022},
  copyright = {CC0},
}