1 citations · 2 across the 3 of their papers we have counts for
4 papers
Strengthening national capability in urban climate science: an Australian perspective
Negin Nazarian, Andy J Pitman, Mathew J Lipson +11
Cities are experiencing significant warming and more frequent climate extremes, raising risks for over 90% of Australians living in cities. Yet many of our tools for climate predic…
Regression on Deep Visual Features using Artificial Neural Networks (ANNs) to Predict Hydraulic Blockage at Culverts
Umair Iqbal, Johan Barthelemy, Wanqing Li +1
Cross drainage hydraulic structures (i.e., culverts, bridges) in urban landscapes are prone to getting blocked by transported debris which often results in causing the flash floods…
Automating Visual Blockage Classification of Culverts with Deep Learning
Umair Iqbal, Johan Barthelemy, Wanqing Li +1
Blockage of culverts by transported debris materials is reported as main contributor in originating urban flash floods. Conventional modelling approaches had no success in addressi…
Prediction of Hydraulic Blockage at Cross Drainage Structures using Regression Analysis
Umair Iqbal, Johan Barthelemy, Pascal Perez +1
Hydraulic blockage of cross-drainage structures such as culverts is considered one of main contributor in triggering urban flash floods. However, due to lack of during floods data…