Peng Dai

771 citations
22 papers · 528 · h-index 10

Impact in

Papers in

Peng Dai

17 papers receiving 513 citations

Peers

Peng Dai
Comparison fields: 5 of 68
  • Transportation 93
  • Building and Construction 147
  • Civil and Structural Engineering 141
  • Industrial and Manufacturing Engineering 64
  • Media Technology 44
Replace Guiping Wang with:
Guiping Wang China
Gabriel Michau Switzerland
Jiang Liu China
Jianying Zheng China
Xinxin Yan China
Arman Malekloo Türkiye
Xili Wan China
Jian Miao China
Vilmos Simon Hungary
Hye-Won Lee South Korea
Peng Dai relative to Guiping Wang China Guiping Wang's profile →
Citations per field
00.5×3.2×
Guiping Wang · 1×
Citations per year

Countries citing papers authored by Peng Dai

Since Specialization
Citations

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

Fields of papers citing papers by Peng Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021142
2 2020134
3 201967
4 201742
5 201738
6 201925
7 202218
8 201614
9 201812
10 202010
11 20237
12 20197
13 20195
14 20093
15 20221
16 20201
17 20091
18 20121
19 20250
20 20230

About Peng Dai

Peng Dai is a scholar working on Civil and Structural Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition, Media Technology and Electrical and Electronic Engineering, having authored 22 papers that have together received 528 indexed citations. Recurring topics across this work include Infrastructure Maintenance and Monitoring (8 papers), Railway Engineering and Dynamics (6 papers), Vehicle License Plate Recognition (6 papers), Industrial Vision Systems and Defect Detection (4 papers), Advanced Measurement and Detection Methods (4 papers), Non-Destructive Testing Techniques (2 papers), Human Mobility and Location-Based Analysis (2 papers) and Traffic Prediction and Management Techniques (2 papers). The work is most often cited by research in Transportation (93 citations), Building and Construction (147 citations), Civil and Structural Engineering (141 citations), Industrial and Manufacturing Engineering (64 citations) and Media Technology (44 citations). Peng Dai has collaborated with scholars based in China, United States and Belgium. Frequent co-authors include Shengchun Wang, Liefeng Bo, Chao Huang, Xinyu Du, Yunlai Zhou, Magd Abdel Wahab, Lianghao Xia, Yu Zheng, Junbo Zhang and Xiyue Zhang. Their work appears in journals such as Applied Sciences, Future Generation Computer Systems, Computer-Aided Civil and Infrastructure Engineering, Measurement and IET Control Theory and 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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