University of Reading Research Data Archive

Deep learning for the estimation of water-levels using river cameras: networks and datasets

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Description

This dataset contains:
- The networks weights (weights.zip) that were obtained and used in our papers [1, 2]. We refer to these papers for the methodology used to obtain those weights. Those weights can be used for the binary water semantic segmentation of new images, or for comparison with our methods.
- The river camera images (DIGLIS.zip/EVESHAM.zip/STRENSHAM.zip/TEWKESBURY.zip) for the experiments that we presented in [2]. The images can be used for water segmentation and flood analysis purposes.

Related publications:
[1] Remy Vandaele, Sarah L. Dance, Varun Ojha; Automated water segmentation and river level detection on camera images using transfer learning; 2020; Proceedings of the DAGM German Conference on Pattern Recognition (Accepted)
[2] Remy Vandaele, Sarah L. Dance, Varun Ojha; Deep learning for the estimation of water-levels using river cameras; 2020; Hydrology and Earth System Science (in preparation)

Resource Type: Dataset
Creators: Vandaele, Remy, Dance, Sarah and Ojha, Varun
Rights-holders: University of Reading, Farson Digital Limited
Data Publisher: University of Reading
Publication Date: 2021
Data last accessed: 7 April 2021
DOI: http://dx.doi.org/10.17864/1947.282
Metadata Record URL: https://researchdata.reading.ac.uk/id/eprint/282
Organisational units: Science > School of Mathematical, Computational and Physical Sciences > Department of Mathematics and Statistics
Science > School of Mathematical, Computational and Physical Sciences > Department of Computer Science
Science > School of Mathematical, Computational and Physical Sciences > Department of Meteorology
Participating Organisations: University of Reading, Farson Digital Limited
Keywords: water segmentation, river camera images, river-level estimation
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