55 citations as recorded by crossref.

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16. Assessment of a Machine Learning Algorithm Using Web Images for Flood Detection and Water Level Estimates M. Tedesco & J. Radzikowski
17. Error-correction across gauged and ungauged locations: A data assimilation-inspired approach to post-processing river discharge forecasts G. Matthews et al.
18. Temporary flood marks proposal: What we learned after losing the baroque artifact from Cracow, Poland R. Szczepanek et al.
19. Evaluation of deep learning computer vision for water level measurements in rivers W. Liu & W. Huang
20. Application of Closed-Circuit Television Image Segmentation for Irrigation Channel Water Level Measurement K. Kim & J. Choi
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22. Deep Learning to Recognize Water Level for Agriculture Reservoir Using CCTV Imagery S. Kwon & S. Lee
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25. Unlocking flow–habitat relationships in mountain rivers of Epirus, Greece using object detection and hydrodynamic simulation C. Papadaki et al.
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29. Urban flood extent segmentation and evaluation from real-world surveillance camera images using deep convolutional neural network Y. Wang et al.
30. Technical note: A low-cost approach to monitoring relative streamflow dynamics in small headwater streams using time lapse imagery and a deep learning model P. Goodling et al.
31. Eye of Horus: a vision-based framework for real-time water level measurement S. Erfani et al.
32. Latent data assimilation with non‐explicit observation operator in hydrology K. Wang et al.
33. Stochastic properties of coastal flooding events – Part 1: convolutional-neural-network-based semantic segmentation for water detection B. Kang et al.
34. Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning☆ P. Malekzadeh et al.
35. Dynamic Modeling of Water Level Changes Using Image Processing and Machine Learning E. Abdi et al.
36. Practical application of time-lapse camera imagery to develop water-level data for three hydrologic monitoring sites in Wisconsin during water year 2020 K. Johnson et al.
37. Ensuring reliable water level measurement for flooding: A redundancy-based approach with pressure transducer and computer vision S. Matos et al.
38. Assessing Deep Learning Techniques for Remote Gauging and Water Quality Monitoring Using Webcam Images R. Xu & B. Wang
39. Calibrated river-level estimation from river cameras using convolutional neural networks R. Vandaele et al.
40. Community-scale urban flood monitoring through fusion of time-lapse imagery, terrestrial lidar, and remote sensing data J. Dale et al.
41. Predicting Dynamic Riverine Nitrogen Export in Unmonitored Watersheds: Leveraging Insights of AI from Data-Rich Regions R. Xiong et al.
42. Advancing river monitoring using image-based techniques: challenges and opportunities S. Manfreda et al.
43. Stage and discharge prediction from documentary time-lapse imagery K. Chapman et al.
44. Do we need to label large datasets for river water segmentation? Benchmark and stage estimation with minimum to non-labeled image time series P. Zamboni et al.
45. A deep learning workflow enhanced with optical flow fields for flood risk estimation C. Ranieri et al.
46. A Comparative Performance Analysis of Popular Deep Learning Models and Segment Anything Model (SAM) for River Water Segmentation in Close-Range Remote Sensing Imagery A. Moghimi et al.
47. Refraction-based waterlogging depth measurement using solely traffic cameras for transparent flood monitoring J. Qin & P. Shen
48. Bringing vision to climate: A hierarchical model for water depth monitoring in headwater streams X. Zhao et al.
49. A novel framework for automated water level estimation using CCTV imagery in Yongseong Agricultural Reservoir, South Korea S. Kwon et al.
50. Improving heat transfer predictions in heterogeneous riparian zones using transfer learning techniques A. Jin et al.
51. Deep Learning-Based Enhancement for Surface Velocity Measurements in Tidal Estuaries W. Huang et al.
52. Deep learning for automated trash screen blockage detection using cameras: Actionable information for flood risk management R. Vandaele et al.
53. Deep Learning Semantic Segmentation for Water Level Estimation Using Surveillance Camera N. Muhadi et al.
54. Development of Deep Intelligence for Automatic River Detection (RivDet) S. Lee et al.
55. RivAIr: A custom-designed UAV-based sensor for real-time water area segmentation and surface velocity estimation M. Salandra et al.