Lin Wei

1.1k citations
62 papers · 739 · 1 hit paper · h-index 13

Impact in

Papers in

Lin Wei

57 papers receiving 696 citations

Lin Wei's Hit Papers

Detecting fake news by exploring the consistency of multimodal data 2021 · 167 citations
1670+1+3Years since publication50100150

Peers

Lin Wei
Comparison fields: 5 of 110
  • Signal Processing 105
  • Artificial Intelligence 291
  • Computer Vision and Pattern Recognition 169
  • Computer Networks and Communications 170
  • Information Systems 159
Replace Jihong Ouyang with:
Jihong Ouyang China
Yi Zhuang China
Subrota Kumar Mondal Macao
Satya Prakash Ghrera India
Martin Loomes United Kingdom
Farhan Amin South Korea
El-Sayed M. El-Horbaty Egypt
Lin Wei relative to Jihong Ouyang China Jihong Ouyang's profile →
Citations per field
00.5×3.3×
Jihong Ouyang · 1×
Citations per year

Countries citing papers authored by Lin Wei

Since Specialization
Citations

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

Fields of papers citing papers by Lin Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Detecting fake news by exploring the consistency of multimodal data
Hit paper breakdown →
2021167
2 201084
3 199169
4 199160
5 202247
6 200838
7 199137
8 201719
9 202118
10 199517
11 200412
12 201012
13 202112
14 198810
15 20179
16 20209
17 20058
18 20198
19 20098
20 20067

About Lin Wei

Lin Wei is a scholar working on Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Information Systems, having authored 62 papers that have together received 739 indexed citations. Recurring topics across this work include Caching and Content Delivery (9 papers), Sentiment Analysis and Opinion Mining (7 papers), Peer-to-Peer Network Technologies (6 papers), Advanced Vision and Imaging (5 papers), Network Security and Intrusion Detection (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Cognitive Radio Networks and Spectrum Sensing (4 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Signal Processing (105 citations), Artificial Intelligence (291 citations), Computer Vision and Pattern Recognition (169 citations), Computer Networks and Communications (170 citations) and Information Systems (159 citations). Lin Wei has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Qinyu Zhang, Lei Shi, C.-T. Chen, Yafei Li, Yichen Tian, Junxiao Xue, Yujie Tang, Jie Feng, Eric Chen-Kuo Tsao and Yufei Gao. Their work appears in journals such as IEEE Transactions on Nuclear Science, Electronics, Journal of Telemedicine and Telecare, PeerJ Computer Science and Expert Systems with Applications.

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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