Ke Wu

53 papers receiving 1.0k citations

Hit Papers

False rumors detection on Sina Weibo by propagation structures 2015 · 380 citations
3800+3+7Years since publication100200300

Peers

Ke Wu
Comparison fields: 5 of 93
  • Media Technology 435
  • Atmospheric Science 251
  • Statistical and Nonlinear Physics 172
  • Artificial Intelligence 315
  • Information Systems 211
Replace Roberto Interdonato with:
Roberto Interdonato France
Wei Tian China
Kunlun Qi China
Ranga Raju Vatsavai United States
Laure Berti‐Équille France
Zhongliang Wei China
Shyam Boriah United States
Kamalika Das United States
Jinbao Wang China
Jiyuan Liu China
Ke Wu relative to Roberto Interdonato France Roberto Interdonato's profile →
Citations per field
00.5×3.1×
Roberto Interdonato · 1×
Citations per year

Countries citing papers authored by Ke Wu

Since Specialization
Citations

This map shows the geographic impact of Ke 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 Ke Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ke Wu more than expected).

Fields of papers citing papers by Ke Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ke 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 Ke Wu. The network helps show where Ke Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Ke 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 Ke Wu Line = papers co-authored together Ke Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1
False rumors detection on Sina Weibo by propagation structures
Hit paper breakdown →
2015380
2 2008144
3 201974
4 201736
5 201935
6 202130
7 201728
8 201725
9 201723
10 202219
11 201117
12 201416
13 201715
14 202115
15 201715
16
Cross-Language Entity Linking in Maryland during a Hurricane.
201112
17 201812
18 202211
19
Cross Language Text Categorization Using a Bilingual Lexicon
200810
20 202010

About Ke Wu

Ke Wu is a scholar working on Media Technology, Atmospheric Science, Computer Vision and Pattern Recognition, Artificial Intelligence and Ecology, having authored 57 papers that have together received 1.1k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (38 papers), Remote Sensing and Land Use (28 papers), Advanced Image Fusion Techniques (13 papers), Remote Sensing in Agriculture (7 papers), Infrared Target Detection Methodologies (6 papers), Natural Language Processing Techniques (4 papers), Text and Document Classification Technologies (4 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Media Technology (435 citations), Atmospheric Science (251 citations), Statistical and Nonlinear Physics (172 citations), Artificial Intelligence (315 citations) and Information Systems (211 citations). Ke Wu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Kenny Q. Zhu, Song Yang, Yuxiang Zhang, Yanfei Zhong, Liangpei Zhang, Pingxiang Li, Xiangyun Hu, Yanni Dong, Bo Du and Qian Du. Their work appears in journals such as Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Geoscience and Remote Sensing Letters, Soft Computing and IEEE Transactions on Geoscience and Remote Sensing.

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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