https://doi.org/10.25678/000150

Data for: Scalable Flood Level Trend Monitoring with Surveillance Cameras using a Deep Convolutional Neural Network

This package provides material that can be openly published for the paper "Scalable Flood Level Trend Monitoring with Surveillance Cameras using a Deep Convolutional Neural Network". It consists in the code used to generate results and figures as well as the weights of the deep convolutional neural networks trained to segment water in the surveillance camera images.

Data and Resources

Citation

This Data Package

Moy de Vitry, M. (2019). Data for: Scalable Flood Level Trend Monitoring with Surveillance Cameras using a Deep Convolutional Neural Network [Version 2] [Data set]. Eawag: Swiss Federal Institute of Aquatic Science and Technology. https://doi.org/10.25678/000150

The associated article

Moy de Vitry, M., S. Kramer, J. D. Wegner, and J. P. Leitão (2019), Scalable Flood Level Trend Monitoring with Surveillance Cameras using a Deep Convolutional Neural Network, Hydrology and Earth System Sciences Discussions, 1–21, doi:10.5194/hess-2018-570.

Metadata

  Publication Data Package for:
Open Data Open Data
Author(s)
  • Moy de Vitry, Matthew
Keywords Flood Trend,deep convolutional neural network,flash flood,image segmentation,none
Systems
  • metropolitan area
  • Urban Drainage System
Timerange
  • *
Review Level none
Curator Moy de Vitry, Matthew
Contact matthew.moydevitry@eawag.ch
DOI 10.25678/000150