Cheng Da

669 citations
40 papers · 369 indexed · h-index 11

Impact in

Papers in

Cheng Da

38 papers receiving 354 citations

Peers

Cheng Da
Comparison fields: 5 of 73
  • Computer Vision and Pattern Recognition 96
  • Soil Science 27
  • Plant Science 92
  • General Agricultural and Biological Sciences 20
  • Aerospace Engineering 57
Replace John A. Belward with:
John A. Belward Australia
Wei Xue China
H. Have Hungary
Gerardo Hernández Mexico
Waqas Ahmed Malik Germany
Jian Jin United States
Yufeng Yang China
Jérémie T. Zoueu Ivory Coast
Shahid Khattak Pakistan
Hongping Yan China
Cheng Da relative to John A. Belward Australia John A. Belward's profile →
Citations per field
00.5×3.8×
John A. Belward · 1×
Citations per year

Countries citing papers authored by Cheng Da

Since Specialization
Citations

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

Fields of papers citing papers by Cheng Da

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201634
2 201734
3 201627
4 201423
5 201522
6 201921
7 201515
8 201813
9 201712
10 201910
11 201410
12 201510
13 202110
14 20189
15 20239
16 20189
17 20199
18 20168
19 20168
20 20238

About Cheng Da

Cheng Da is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Aerospace Engineering, Computer Vision and Pattern Recognition and Plant Science, having authored 40 papers that have together received 369 indexed citations. Recurring topics across this work include Particle accelerators and beam dynamics (12 papers), Superconducting Materials and Applications (12 papers), Particle Accelerators and Free-Electron Lasers (9 papers), Advanced Image and Video Retrieval Techniques (5 papers), Multimodal Machine Learning Applications (4 papers), Microgrid Control and Optimization (2 papers), Agriculture Sustainability and Environmental Impact (2 papers) and Plant Stress Responses and Tolerance (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (96 citations), Soil Science (27 citations), Plant Science (92 citations), General Agricultural and Biological Sciences (20 citations) and Aerospace Engineering (57 citations). Cheng Da has collaborated with scholars based in China, United States and Cayman Islands. Frequent co-authors include Chunhong Pan, Shiming Xiang, Caihong Li, Gaoming Jiang, Gaofeng Meng, Liyue Guo, Guanglei Wu, Shibiao Xu, Xiaofan Yu and Kun Ding. Their work appears in journals such as IEEE Transactions on Applied Superconductivity, Cryogenics, International Journal of Modern Physics A, PeerJ and Scientific Reports.

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.

Explore authors with similar magnitude of impact