Publication: Automatic water-level class estimation from repeated crowd-based photos of streams
Automatic water-level class estimation from repeated crowd-based photos of streams
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Wang, Z., Seibert, J., van Meerveld, H. J., Lyu, H., & Zhang, C. (2023). Automatic water-level class estimation from repeated crowd-based photos of streams. Hydrological Sciences Journal, 68, 1826–1840. https://doi.org/10.1080/02626667.2023.2240312
Abstract
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Abstract
Citizen science projects engage the public in monitoring the environment and can collect useful data. One example is the CrowdWater project, in which stream levels are observed and compared to reference photos taken at an earlier time to obtain stream level class data. However, crowd-based observations are uncertain and require data quality control. Therefore, we used a deep learning model to estimate the water-level class for photos taken by citizen scientists at different times for the same stream and compared different options for
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- Wang, Ze
- Lyu, Heng
- Zhang, Chi
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Wang, Z., Seibert, J., van Meerveld, H. J., Lyu, H., & Zhang, C. (2023). Automatic water-level class estimation from repeated crowd-based photos of streams. Hydrological Sciences Journal, 68, 1826–1840. https://doi.org/10.1080/02626667.2023.2240312
