Lan Dong

459 citations
18 papers · 160 · h-index 7

Impact in

Papers in

Lan Dong

16 papers receiving 152 citations

Peers

Lan Dong
Comparison fields: 5 of 36
  • Computer Vision and Pattern Recognition 98
  • Artificial Intelligence 65
  • Radiation 10
  • Media Technology 7
  • Statistics, Probability and Uncertainty 5
Replace Tatjana Chavdarova with:
Tatjana Chavdarova Switzerland
L. Manhaes de Andrade Filho Brazil
Yuzhang Gu China
Yifan Jiang United States
M. Licata United Kingdom
Yuewen Ma China
Dongkai Wang China
Utkarsh Sinha India
Lan Dong relative to Tatjana Chavdarova Switzerland Tatjana Chavdarova's profile →
Citations per field
00.5×
Tatjana Chavdarova · 1×
Citations per year

Countries citing papers authored by Lan Dong

Since Specialization
Citations

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

Fields of papers citing papers by Lan Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 200776
2 202221
3 202310
4 20259
5 20236
6 20216
7 20066
8 20076
9 20115
10 20065
11 20213
12 20252
13 20232
14 20251
15 20211
16 20171
17 20240
18 20240

About Lan Dong

Lan Dong is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Electrical and Electronic Engineering, Biomedical Engineering and Artificial Intelligence, having authored 18 papers that have together received 160 indexed citations. Recurring topics across this work include Particle Accelerators and Free-Electron Lasers (5 papers), Superconducting Materials and Applications (4 papers), Advanced SAR Imaging Techniques (3 papers), Advanced Vision and Imaging (3 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (3 papers), Video Surveillance and Tracking Methods (3 papers), Optical Systems and Laser Technology (2 papers) and Optical measurement and interference techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (98 citations), Artificial Intelligence (65 citations), Radiation (10 citations), Media Technology (7 citations) and Statistics, Probability and Uncertainty (5 citations). Lan Dong has collaborated with scholars based in China and United States. Frequent co-authors include Vasu Parameswaran, Visvanathan Ramesh, S.C. Schwartz, Daiyin Zhu, Xinhua Mao, Zhenqiang He, Xiaoyang Liu, Xiaolong Wang, Sheng Liu and Minxian Li. Their work appears in journals such as Measurement Science and Technology, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, IEEE Geoscience and Remote Sensing Letters, International Journal of Computer Assisted Radiology and Surgery and Measurement.

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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