Weichen Dai

678 citations
28 papers · 418 · h-index 9

Impact in

Papers in

Weichen Dai

22 papers receiving 407 citations

Peers

Weichen Dai
Comparison fields: 5 of 58
  • Geology 71
  • Computer Vision and Pattern Recognition 215
  • Aerospace Engineering 215
  • Surfaces, Coatings and Films 32
  • Acoustics and Ultrasonics 3
Replace Zhiqiang Yan with:
Zhiqiang Yan China
Masanori Idesawa Japan
Fang Xu United States
Faysal Boughorbel United States
Motoharu Fujigaki Japan
Katsushi Ikeuchi Japan
Nathan Kirchner Australia
Katsuhiko Sakaue Japan
Matt Brand United States
Lianqing Zhu China
Weichen Dai relative to Zhiqiang Yan China Zhiqiang Yan's profile →
Citations per field
00.5×5.8×
Zhiqiang Yan · 1×
Citations per year

Countries citing papers authored by Weichen Dai

Since Specialization
Citations

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

Fields of papers citing papers by Weichen Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020160
2 200647
3 200938
4 202334
5 202226
6 202226
7 202114
8 201910
9 20109
10 20218
11 20087
12 20217
13 20225
14 20195
15 20235
16 20224
17 20184
18 20243
19 20082
20 20241

About Weichen Dai

Weichen Dai is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Biomedical Engineering, having authored 28 papers that have together received 418 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (14 papers), Advanced Vision and Imaging (10 papers), Advanced Image and Video Retrieval Techniques (7 papers), Photonic Crystals and Applications (5 papers), Plasmonic and Surface Plasmon Research (4 papers), Photonic and Optical Devices (4 papers), Robotic Path Planning Algorithms (3 papers) and 3D Surveying and Cultural Heritage (3 papers). The work is most often cited by research in Geology (71 citations), Computer Vision and Pattern Recognition (215 citations), Aerospace Engineering (215 citations), Surfaces, Coatings and Films (32 citations) and Acoustics and Ultrasonics (3 citations). Weichen Dai has collaborated with scholars based in China, United States and Greece. Frequent co-authors include Yu Zhang, Li Ping, Costas M. Soukoulis, Zheng Fang, Sebastian Scherer, Wanzeng Kong, Anan Fang, Thomas Koschny, L. Zhang and G. Tuttle. Their work appears in journals such as IEEE Robotics and Automation Letters, Physical Review B, IEEE Transactions on Pattern Analysis and Machine Intelligence, The Visual Computer and Applied Physics Letters.

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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