Li Song

556 citations
42 papers · 362 indexed · 1 hit paper · h-index 9

Li Song

35 papers receiving 328 citations

Hit Papers

On the use of deep learning for phase recovery104202420262025255075100

Peers

Li Song
Comparison fields: 5 of 77
  • Acoustics and Ultrasonics 15
  • Radiation 59
  • Virology 28
  • Applied Mathematics 61
  • Structural Biology 8
Replace Emrah Bostan with:
Emrah Bostan Switzerland
M. Santarsiero Italy
Hongchen Zhai China
V. Bagini Italy
David M. Strong United States
Glenn A. Tyler United States
G. R. Ayers United Kingdom
Pete Casazza United States
Caojin Yuan China
Li Song relative to Emrah Bostan Switzerland Emrah Bostan's profile →
Citations per field
00.5×4.4×
Emrah Bostan · 1×
Citations per year

Countries citing papers authored by Li Song

Since Specialization
Citations

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

Fields of papers citing papers by Li Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3
On the use of deep learning for phase recoverybreakdown →
2024104
4 20232
5 202336
6 202317
7 20225
8 202214
9 20216
10 202016
11
Spectrum Characteristic of Dissipative Compact Schemes and Application to Couette Flow
20092
12
Compact composition operators on BMOA(B_n)
20091
13 20096
14
An Improved Kirsch Edge Detection Method
20070
15 20073
16 200637
17 19976
18 19971
19 19951
20 19941

About Li Song

Li Song is a scholar working on Radiation, Acoustics and Ultrasonics and Computer Vision and Pattern Recognition, having authored 42 papers that have together received 362 indexed citations. Recurring topics across this work include Advanced X-ray Imaging Techniques (11 papers), Optical measurement and interference techniques (9 papers), Digital Holography and Microscopy (6 papers), Image and Signal Denoising Methods (5 papers), Mathematical Analysis and Transform Methods (5 papers), Approximation Theory and Sequence Spaces (5 papers), Advancements in Photolithography Techniques (3 papers) and Fluid Dynamics and Turbulent Flows (3 papers). The work is most often cited by research in Acoustics and Ultrasonics (15 citations), Radiation (59 citations) and Virology (28 citations). Li Song has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Edmund Y. Lam, Jun Xian, George Barbastathis, Kaiqiang Wang, Chutian Wang, Jiazhen Dou, Renjie Zhou, Jianglei Di, Jianlin Zhao and Zhenbo Ren. Their work appears in journals such as Optics Letters, Optics Express and IEEE Transactions on Antennas and Propagation.

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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