Lingyu Si

499 citations
29 papers · 307 · 1 hit paper · h-index 9

Impact in

Papers in

Lingyu Si

24 papers receiving 302 citations

Lingyu Si's Hit Papers

Part-Aware Correlation Networks for Few-Shot Learning 2024 · 48 citations
480+1Years since publication10203040

Peers

Lingyu Si
Comparison fields: 5 of 70
  • Computer Vision and Pattern Recognition 132
  • Media Technology 31
  • Aerospace Engineering 81
  • Artificial Intelligence 66
  • Safety, Risk, Reliability and Quality 14
Replace Yusheng Xu with:
Yusheng Xu China
Pavan Kumar Anasosalu Vasu United States
Shengcao Cao United States
Xiaoxue Feng China
Zhengwu Yuan China
Yuanjie Dang China
Zonghao Guo China
James Gabriel United States
Indrajit Kurmi Austria
Lingyu Si relative to Yusheng Xu China Yusheng Xu's profile →
Citations per field
00.5×4.7×
Yusheng Xu · 1×
Citations per year

Countries citing papers authored by Lingyu Si

Since Specialization
Citations

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

Fields of papers citing papers by Lingyu Si

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201951
2
Part-Aware Correlation Networks for Few-Shot Learning
Hit paper breakdown →
202448
3 202446
4 202429
5 201828
6 202319
7 202216
8 202410
9 20239
10 20238
11 20238
12 20236
13 20225
14 20234
15 20224
16 20243
17 20243
18 20232
19 20232
20 20222

About Lingyu Si

Lingyu Si is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Oceanography and Media Technology, having authored 29 papers that have together received 307 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (6 papers), Advanced Neural Network Applications (6 papers), Domain Adaptation and Few-Shot Learning (6 papers), Advanced SAR Imaging Techniques (6 papers), Advanced Image and Video Retrieval Techniques (5 papers), Advanced Graph Neural Networks (3 papers), Human Pose and Action Recognition (3 papers) and Underwater Acoustics Research (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (132 citations), Media Technology (31 citations), Aerospace Engineering (81 citations), Artificial Intelligence (66 citations) and Safety, Risk, Reliability and Quality (14 citations). Lingyu Si has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Fuchun Sun, Changwen Zheng, Ruiheng Zhang, Lixin Xu, Wenwen Qiang, Yumeng Liu, Shuo Yang, Hongwei Dong, Lamei Zhang and Jianwei Niu. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Nature Communications, Knowledge-Based Systems and IEEE Transactions on Multimedia.

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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