activity
20212024
most citedSpatio-temporal-spectral-angular observation model that integrates observations from UAV and mobile mapping vehicle for better urban mapping

18 citations · 31 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024

Aquila: A Hierarchically Aligned Visual-Language Model for Enhanced Remote Sensing Image Comprehension

Kaixuan Lu, Ruiqian Zhang, Xiao Huang +1

Recently, large vision language models (VLMs) have made significant strides in visual language capabilities through visual instruction tuning, showing great promise in the field of…

cs.CV20227 cited

RCDT: Relational Remote Sensing Change Detection with Transformer

Kaixuan Lu, Xiao Huang

Deep learning based change detection methods have received wide attentoion, thanks to their strong capability in obtaining rich features from images. However, existing AI-based CD…

cs.CV202118 cited

Spatio-temporal-spectral-angular observation model that integrates observations from UAV and mobile mapping vehicle for better urban mapping

Zhenfeng Shao, Gui Cheng, Deren Li +3

In a complex urban scene, observation from a single sensor unavoidably leads to voids in observations, failing to describe urban objects in a comprehensive manner. In this paper, w…

cs.CY20212 cited

Evaluating the weight sensitivity in AHP-based flood risk estimation models

Hongping Zhang, Zhenfeng Shao, Bin Hua +4

In the analytic hierarchy process (AHP) based flood risk estimation models, it is widely acknowledged that different weighting criteria can lead to different results. In this study…

stat.AP20211 cited

An extended watershed-based zonal statistical AHP model for flood risk estimation: Constraining runoff converging related indicators by sub-watersheds

Hongping Zhang, Zhenfeng Shao, Jinqi Zhao +4

Floods are highly uncertain events, occurring in different regions, with varying prerequisites and intensities. A highly reliable flood disaster risk map can help reduce the impact…

cs.CV2021

Pan-sharpening via High-pass Modification Convolutional Neural Network

Jiaming Wang, Zhenfeng Shao, Xiao Huang +3

Most existing deep learning-based pan-sharpening methods have several widely recognized issues, such as spectral distortion and insufficient spatial texture enhancement, we propose…