activity
20192023
most citedShort-term Hourly Streamflow Prediction with Graph Convolutional GRU Networks

53 citations · 95 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2023★ 2 cited

EfficientTempNet: Temporal Super-Resolution of Radar Rainfall

Bekir Z Demiray, Muhammed Sit, Ibrahim Demir

Rainfall data collected by various remote sensing instruments such as radars or satellites has different space-time resolutions. This study aims to improve the temporal resolution…

eess.IV2021

DEM Super-Resolution with EfficientNetV2

Bekir Z Demiray, Muhammed Sit, Ibrahim Demir

Efficient climate change monitoring and modeling rely on high-quality geospatial and environmental datasets. Due to limitations in technical capabilities or resources, the acquisit…

cs.CV2021★ 1 cited

TempNet -- Temporal Super Resolution of Radar Rainfall Products with Residual CNNs

Muhammed Sit, Bong-Chul Seo, Ibrahim Demir

The temporal and spatial resolution of rainfall data is crucial for environmental modeling studies in which its variability in space and time is considered as a primary factor. Rai…

cs.LG2021★ 53 cited

Short-term Hourly Streamflow Prediction with Graph Convolutional GRU Networks

Muhammed Sit, Bekir Demiray, Ibrahim Demir

The frequency and impact of floods are expected to increase due to climate change. It is crucial to predict streamflow, consequently flooding, in order to prepare and mitigate its…

cs.LG2021★ 35 cited

IowaRain: A Statewide Rain Event Dataset Based on Weather Radars and Quantitative Precipitation Estimation

Muhammed Sit, Bong-Chul Seo, Ibrahim Demir

Effective environmental planning and management to address climate change could be achieved through extensive environmental modeling with machine learning and conventional physical…

physics.geo-ph2020★ 2 cited

A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources

Muhammed Sit, Bekir Z. Demiray, Zhongrun Xiang +3

The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety, and velocity of water-related data are increasing due to large-scale sensor netw…