default author photo

Xinzhe Li

Imperial College London

South Kensington Campus

London, SW7 2AZ

United Kingdom

SCHOLARLY PAPERS

1

DOWNLOADS

30

TOTAL CITATIONS

0

Scholarly Papers (1)

1.

Inpainting U-Net for seamless pedestrian-level wind prediction across urban morphologies

Number of pages: 19 Posted: 30 Jun 2026
Imperial College London, Imperial College London, Imperial College London, Imperial College London, Imperial College London and Imperial College London
Downloads 30

Abstract:

Loading...

pedestrian-level wind prediction, Urban morphology, deep learning, U-Net, inpainting, surrogate modelling