Ning Wu

4.5k citations
244 papers · 3.0k · 2 hit papers · h-index 26

Impact in

Papers in

Ning Wu

227 papers receiving 3.0k citations

Ning Wu's Hit Papers

Semi-Supervised DAS VSP Data Denoising Using Signal and Noise Distribution Difference 2024 · 307 citations
3070+2+4Years since publication100200300

Peers

Ning Wu
Comparison fields: 5 of 166
  • Geophysics 568
  • Computer Vision and Pattern Recognition 683
  • Media Technology 222
  • Signal Processing 223
  • Transportation 136
Replace Jun Liu with:
Jun Liu China
Yilun Wang China
Yongming Huang China
Xiangyang Li China
Hang Zhang China
Brian C. Lovell Australia
Yi Shen China
Yunhai Wang China
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Ning Wu relative to Jun Liu China Jun Liu's profile →
Citations per field
00.5×7.0×
Jun Liu · 1×
Citations per year

Countries citing papers authored by Ning Wu

Since Specialization
Citations

This map shows the geographic impact of Ning Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ning Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ning Wu more than expected).

Fields of papers citing papers by Ning Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ning Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ning Wu. The network helps show where Ning Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Ning Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ning Wu Line = papers co-authored together Ning Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 244 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Semi-Supervised DAS VSP Data Denoising Using Signal and Noise Distribution Difference
Hit paper breakdown →
2024307
2
Distributed Acoustic Sensing Vertical Seismic Profile Data Denoiser Based on Convolutional Neural Network
Hit paper breakdown →
2020205
3 2021133
4 201486
5 202078
6 201975
7 201563
8 201961
9 200459
10 201557
11 200155
12 201154
13 202151
14 201148
15 201346
16 202046
17 202042
18 202440
19 202135
20 201034

About Ning Wu

Ning Wu is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Geophysics, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 244 papers that have together received 3.0k indexed citations. Recurring topics across this work include Seismic Imaging and Inversion Techniques (49 papers), Seismic Waves and Analysis (42 papers), Cryptographic Implementations and Security (21 papers), Image and Signal Denoising Methods (21 papers), Wireless Power Transfer Systems (20 papers), Energy Harvesting in Wireless Networks (20 papers), Advanced Battery Technologies Research (16 papers) and Coding theory and cryptography (14 papers). The work is most often cited by research in Geophysics (568 citations), Computer Vision and Pattern Recognition (683 citations), Media Technology (222 citations), Signal Processing (223 citations) and Transportation (136 citations). Ning Wu has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Yue Li, Yuxing Zhao, Jingyuan Wang, Man Zhang, Juan Li, Tie Zhong, Wayne Xin Zhao, Baojun Yang, Xintong Dong and Hua Huang. Their work appears in journals such as IEEE Geoscience and Remote Sensing Letters, IEEE Transactions on Geoscience and Remote Sensing, Electronics, Geophysics and Journal of Contemporary Brachytherapy.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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