L
Lu Xu
Researcher at Chinese Academy of Sciences
Publications - 19
Citations - 265
Lu Xu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Synthetic aperture radar & Computer science. The author has an hindex of 5, co-authored 19 publications receiving 125 citations.
Papers
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Multi-Temporal SAR Data Large-Scale Crop Mapping Based on U-Net Model
TL;DR: A large-scale crop mapping method using multi-temporal dual-polarization SAR data was proposed and can still achieve better classification performance under the condition of a complex crop planting structure.
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Crop Classification Based on Temporal Information Using Sentinel-1 SAR Time-Series Data
TL;DR: A crop classification scheme, which made full use of multitemporal SAR backscattering responses, and achieved the best overall accuracies in both VH and VV bands is proposed.
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Multitemporal Water Extraction of Dongting Lake and Poyang Lake Based on an Automatic Water Extraction and Dynamic Monitoring Framework
TL;DR: Wang et al. as mentioned in this paper proposed a robust water extraction network (PA-UNet) for automatic extraction and long-term change monitoring of water bodies using Synthetic Aperture Radar (SAR) systems.
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Molecular characterization, receptor binding property, and replication in chickens and mice of H9N2 avian influenza viruses isolated from chickens, peafowls, and wild birds in eastern China.
Jing Guo,Yanwen Wang,Conghui Zhao,Xinxin Gao,Yaping Zhang,Jiqing Li,Mengjing Wang,Hong Zhang,Liu Wenqiang,Chao Wang,Xia Yingju,Lu Xu,Guimei He,Jinyan Shen,Xiaohong Sun,Wenting Wang,Xinyu Han,Xiaoxuan Zhang,Zhengyang Hou,Xinlin Jin,Na Peng,Yubao Li,Guohua Deng,Pengfei Cui,Qianyi Zhang,Xuyong Li,Hualan Chen +26 more
TL;DR: H9N2 avian influenza viruses are widely prevalent in birds and pose an increasing threat to humans because of their enhanced virulence and transmissibility in mammals as mentioned in this paper, and active surveillance on the pr...
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Compact Polarimetric SAR Ship Detection with m-δ Decomposition Using Visual Attention Model
TL;DR: The proposed ship detection algorithm using the pulsed cosine transform (PCT) visual attention model achieves the highest detection rates and the lowest misidentification rate and highest figure of merit, proving the effectiveness of polarimetric information of compact polarIMetric SAR ship detection and the enhancement from the visual attention models.