Cheng Da

682 citations
44 papers · 493 · h-index 13

Impact in

    • Handwritten Text Recognition Techniques
    • Advanced Image and Video Retrieval Techniques
    • Multimodal Machine Learning Applications
    • Image Retrieval and Classification Techniques
    • Image Processing and 3D Reconstruction

Papers in

Cheng Da

42 papers receiving 476 citations

Peers

Cheng Da
Comparison fields: 5 of 77
  • Computer Vision and Pattern Recognition 190
  • Soil Science 28
  • Plant Science 94
  • Agronomy and Crop Science 24
  • General Agricultural and Biological Sciences 20
Replace Xiaobo Sun with:
Xiaobo Sun China
Amar Raheja United States
Zhangliang Chen China
Jian Jin United States
Gerardo Hernández Mexico
P. Punitha India
Neha Goyal India
Matthias Mühlich Germany
Anshu Singla India
Shahid Khattak Pakistan
Cheng Da relative to Xiaobo Sun China Xiaobo Sun's profile →
Citations per field
00.5×12×
Xiaobo Sun · 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 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202246
2 201737
3 201636
4 201629
5 202227
6 201425
7 201524
8 201922
9 202320
10 201415
11 201515
12 201813
13 201712
14 202312
15 201912
16 202112
17 201411
18 201910
19 201510
20 20189

About Cheng Da

Cheng Da is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Biomedical Engineering, Aerospace Engineering and Plant Science, having authored 44 papers that have together received 493 indexed citations. Recurring topics across this work include Superconducting Materials and Applications (12 papers), Particle accelerators and beam dynamics (12 papers), Particle Accelerators and Free-Electron Lasers (9 papers), Advanced Image and Video Retrieval Techniques (6 papers), Handwritten Text Recognition Techniques (4 papers), Multimodal Machine Learning Applications (4 papers), Image Retrieval and Classification Techniques (3 papers) and Islanding Detection in Power Systems (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (190 citations), Soil Science (28 citations), Plant Science (94 citations), Agronomy and Crop Science (24 citations) and General Agricultural and Biological Sciences (20 citations). Cheng Da has collaborated with scholars based in China, United States and Cayman Islands. Frequent co-authors include Peng Wang, Cong Yao, Chunhong Pan, Shiming Xiang, Caihong Li, Gaoming Jiang, Gaofeng Meng, Liyue Guo, Guanglei Wu and Xiaofan Yu. Their work appears in journals such as IEEE Transactions on Applied Superconductivity, Cryogenics, International Journal of Modern Physics A, Photosynthetica and Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment.

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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