Articles | Volume 27, issue 22
Research article
15 Nov 2023
Research article |  | 15 Nov 2023

Eye of Horus: a vision-based framework for real-time water level measurement

Seyed Mohammad Hassan Erfani, Corinne Smith, Zhenyao Wu, Elyas Asadi Shamsabadi, Farboud Khatami, Austin R. J. Downey, Jasim Imran, and Erfan Goharian

Data sets

smhassanerfani/horus: Pre-release version (v1.0.0-alpha) S. M. H. Erfani

Short summary
Predicting flood magnitude and location helps decision-makers to better prepare for flood events. To increase the speed and availability of data during flooding, this study presents a vision-based framework for measuring water levels and detecting floods. The deep learning models use time-lapse images captured by surveillance cameras to detect water extent using semantic segmentation and to transform them into water level values with the help of lidar data.