80 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of TwenteNL5 papers
- Chinese Academy of SciencesCN2 papers
- China Institute of Water Resources and Hydropower ResearchCN1 paper
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE1 paper
- Institute of Geographic Sciences and Natural Resources ResearchCN1 paper
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and ApplicationCN1 paper
- King Abdullah University of Science and TechnologySA1 paper
- Ministry of Water Resources of the People's Republic of ChinaCN1 paper
- NSF National Center for Atmospheric ResearchUS1 paper
- Shanghai Jiao Tong UniversityCN1 paper
- Southwest Petroleum UniversityCN1 paper
- State Key Laboratory of Basin Water Cycle Simulation and Regulation1 paper
5 papers
Space-time clustering of flash floods in a changing climate (China, 1950-2015)
Nan Wang, Luigi Lombardo, Marj Tonini +3
The persistence over space and time of flash flood disasters -- flash floods that have caused either economical or life losses, or both -- is a diagnostic measure of areas subjecte…
On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AID
Yang Long, Gui-Song Xia, Shengyang Li +5
The past years have witnessed great progress on remote sensing (RS) image interpretation and its wide applications. With RS images becoming more accessible than ever before, there…
Shifting velocity of temperature extremes under climate change
Joan Rey, Guillaume Rohat, Marjorie Perroud +2
Rapid changes in climatic conditions threaten both socioeconomic and ecological systems, as these might not be able to adapt or to migrate at the same pace as that of global warmin…
Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides
Luigi Lombardo, Haakon Bakka, Hakan Tanyas +3
In this paper, we investigate earthquake-induced landslides using a geostatistical model that includes a latent spatial effect (LSE). The LSE represents the spatially structured re…
Unsupervised Deep Domain Adaptation for Pedestrian Detection
Lihang Liu, Weiyao Lin, Lisheng Wu +2
This paper addresses the problem of unsupervised domain adaptation on the task of pedestrian detection in crowded scenes. First, we utilize an iterative algorithm to iteratively se…