Ling Ding

1.6k citations
45 papers · 1.2k · 2 hit papers · h-index 14

Impact in

Papers in

Ling Ding

41 papers receiving 1.2k citations

Ling Ding's Hit Papers

Automated pavement crack detection and segmentation based on two-step convolutional neural network 2020 · 286 citations
2860+2+4Years since publication50100150200250

Peers

Ling Ding
Comparison fields: 5 of 95
  • Civil and Structural Engineering 515
  • Control and Systems Engineering 445
  • Industrial and Manufacturing Engineering 127
  • Mechanical Engineering 367
  • Geology 46
Replace Juan Chiachío with:
Juan Chiachío Spain
Manuel Chiachío Spain
P. Sharafi Australia
Xianguang Kong China
Hunhee Cho South Korea
Chong Chen China
Yasser Mohamed Canada
Hsing‐Chih Tsai Taiwan
Jesús María Pinar-Pérez Spain
Ulrich Hermann Canada
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Citations per field
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Citations per year

Countries citing papers authored by Ling Ding

Since Specialization
Citations

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

Fields of papers citing papers by Ling Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Automated pavement crack detection and segmentation based on two-step convolutional neural network
Hit paper breakdown →
2020286
2
Imbalanced Fault Diagnosis of Rolling Bearing Based on Generative Adversarial Network: A Comparative Study
Hit paper breakdown →
2019219
3 2021139
4 2019101
5 202084
6 202280
7 202136
8 201830
9 201729
10 201726
11 202123
12 200920
13 202317
14 202215
15 200913
16 202011
17 202510
18 20249
19 20159
20 20248

About Ling Ding

Ling Ding is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering, Civil and Structural Engineering, Media Technology and Mechanical Engineering, having authored 45 papers that have together received 1.2k indexed citations. Recurring topics across this work include Infrastructure Maintenance and Monitoring (12 papers), Robotic Mechanisms and Dynamics (7 papers), Asphalt Pavement Performance Evaluation (7 papers), Industrial Vision Systems and Defect Detection (5 papers), Manufacturing Process and Optimization (5 papers), Piezoelectric Actuators and Control (5 papers), Machine Fault Diagnosis Techniques (4 papers) and 3D Surveying and Cultural Heritage (4 papers). The work is most often cited by research in Civil and Structural Engineering (515 citations), Control and Systems Engineering (445 citations), Industrial and Manufacturing Engineering (127 citations), Mechanical Engineering (367 citations) and Geology (46 citations). Ling Ding has collaborated with scholars based in China, Australia and Canada. Frequent co-authors include Wentao Mao, Vincent C. S. Lee, Yamin Liu, Xu Yang, Yuan Li, Xihui Liang, Jinchao Guan, Xin Wang, Sang Luo and Jingwei Liu. Their work appears in journals such as Automation in Construction, Computer-Aided Civil and Infrastructure Engineering, Sustainability, Robotica and Journal of Mechanisms and Robotics.

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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