Songyu Yu

181 total papers · 1.0k total citations
107 papers, 713 citations indexed

About

Songyu Yu is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Songyu Yu has authored 107 papers receiving a total of 713 indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Computer Vision and Pattern Recognition, 39 papers in Signal Processing and 24 papers in Computer Networks and Communications. Recurrent topics in Songyu Yu's work include Video Coding and Compression Technologies (33 papers), Advanced Data Compression Techniques (32 papers) and Image and Video Quality Assessment (19 papers). Songyu Yu is often cited by papers focused on Video Coding and Compression Technologies (33 papers), Advanced Data Compression Techniques (32 papers) and Image and Video Quality Assessment (19 papers). Songyu Yu collaborates with scholars based in China, United States and Canada. Songyu Yu's co-authors include Xiaokang Yang, Yi Xu, Zhaowen Wang, Li Song, Yi Sun, Rui Zhang, Chen Wang, Yunqiang Liu, Yue Wang and Hongkai Xiong and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Transactions on Image Processing and Physical Review A.

In The Last Decade

Songyu Yu

97 papers receiving 661 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Songyu Yu 544 213 162 97 90 107 713
Maria Paula Queluz 500 0.9× 126 0.6× 186 1.1× 124 1.3× 108 1.2× 76 733
Shih‐Chang Hsia 407 0.7× 238 1.1× 200 1.2× 81 0.8× 51 0.6× 107 768
Pengwei Hao 653 1.2× 328 1.5× 64 0.4× 133 1.4× 71 0.8× 66 890
Yilin Chang 246 0.5× 146 0.7× 367 2.3× 59 0.6× 298 3.3× 71 731
G. Calvagno 726 1.3× 226 1.1× 72 0.4× 276 2.8× 43 0.5× 80 865
D.R. Bull 483 0.9× 178 0.8× 87 0.5× 263 2.7× 45 0.5× 65 695
Young Hwan Kim 383 0.7× 108 0.5× 199 1.2× 60 0.6× 57 0.6× 113 777
Jin-Jang Leou 687 1.3× 301 1.4× 42 0.3× 112 1.2× 28 0.3× 66 764
Dong-Wook Kim 413 0.8× 113 0.5× 105 0.6× 244 2.5× 46 0.5× 112 715
R. Aravind 480 0.9× 290 1.4× 145 0.9× 54 0.6× 127 1.4× 56 697

Countries citing papers authored by Songyu Yu

Since Specialization
Citations

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

Fields of papers citing papers by Songyu Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Songyu Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Songyu Yu. A scholar is included among the top collaborators of Songyu Yu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Songyu Yu. Songyu Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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