Wei Dai

1.2k citations
91 papers · 827 · h-index 15

Impact in

Papers in

    • Advanced Data Compression Techniques 20
    • Advanced Vision and Imaging 17
    • Advanced Image Processing Techniques 10
    • Image and Video Quality Assessment 9
    • Robotic Path Planning Algorithms 7
    • Video Coding and Compression Technologies 26

Wei Dai

82 papers receiving 792 citations

Peers

Wei Dai
Comparison fields: 5 of 129
  • Computational Mathematics 23
  • Signal Processing 199
  • Computer Vision and Pattern Recognition 345
  • Media Technology 129
  • Computer Networks and Communications 122
Replace Qiang Cheng with:
Qiang Cheng United States
Dengyong Zhang China
Xiaoyu Du China
Rongyao Hu China
Donggyu Joo South Korea
Chunfeng Yuan China
Xinyu Liu China
Wei Dai relative to Qiang Cheng United States Qiang Cheng's profile →
Citations per field
00.5×3.9×
Qiang Cheng · 1×
Citations per year

Countries citing papers authored by Wei Dai

Since Specialization
Citations

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

Fields of papers citing papers by Wei Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016131
2 202055
3 202049
4 201949
5 201837
6 201930
7 200328
8 201521
9 200420
10 201218
11 201217
12 200317
13 201316
14 201215
15 200515
16 201814
17 202012
18 202412
19 201212
20 201911

About Wei Dai

Wei Dai is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Computer Networks and Communications and Information Systems, having authored 91 papers that have together received 827 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (26 papers), Advanced Data Compression Techniques (20 papers), Advanced Vision and Imaging (17 papers), Advanced Image Processing Techniques (10 papers), Image and Video Quality Assessment (9 papers), Robotic Path Planning Algorithms (7 papers), Service-Oriented Architecture and Web Services (6 papers) and Intracranial Aneurysms: Treatment and Complications (6 papers). The work is most often cited by research in Computational Mathematics (23 citations), Signal Processing (199 citations), Computer Vision and Pattern Recognition (345 citations), Media Technology (129 citations) and Computer Networks and Communications (122 citations). Wei Dai has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Gongjian Wen, Xing Zhang, Huimin Lu, Oscar C. Au, Zhiqiang Zheng, Junhao Xiao, Zhiwen Zeng, Trac D. Tran, Weijia Yao and Sijin Li. Their work appears in journals such as Journal of Intelligent & Robotic Systems, IEEE Robotics and Automation Letters, Journal of Integrative Neuroscience, World Neurosurgery and Electronics.

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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