Shi-Nine Yang

41 total papers · 673 total citations
32 papers, 434 citations indexed

About

Shi-Nine Yang is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Shi-Nine Yang has authored 32 papers receiving a total of 434 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 7 papers in Control and Systems Engineering and 7 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Shi-Nine Yang's work include Video Analysis and Summarization (9 papers), Advanced Image and Video Retrieval Techniques (8 papers) and Human Motion and Animation (7 papers). Shi-Nine Yang is often cited by papers focused on Video Analysis and Summarization (9 papers), Advanced Image and Video Retrieval Techniques (8 papers) and Human Motion and Animation (7 papers). Shi-Nine Yang collaborates with scholars based in Taiwan, United States and Germany. Shi-Nine Yang's co-authors include Chih‐Yi Chiu, Hsin-Chih Lin, Lingling Wang, Mingyang Wu, Lingling Wang, Lingling Wang, Weichang Du, Mao‐Jiun J. Wang, Jun-Ming Lu and Wen‐Yen Wu and has published in prestigious journals such as IEEE Transactions on Image Processing, Pattern Recognition Letters and Signal Processing.

In The Last Decade

Shi-Nine Yang

28 papers receiving 395 citations

Author Peers

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

Author Last Decade Papers Cites
Shi-Nine Yang 307 81 65 37 35 32 434
Yonggen Ling 301 1.0× 51 0.6× 35 0.5× 15 0.4× 18 0.5× 30 366
Lei Han 280 0.9× 53 0.7× 101 1.6× 12 0.3× 50 1.4× 37 477
D. Nitzan 286 0.9× 56 0.7× 21 0.3× 26 0.7× 17 0.5× 19 467
Xun Xu 249 0.8× 49 0.6× 164 2.5× 19 0.5× 24 0.7× 28 492
ShahRukh Athar 235 0.8× 30 0.4× 52 0.8× 30 0.8× 26 0.7× 17 407
Asif Masood 249 0.8× 42 0.5× 71 1.1× 12 0.3× 34 1.0× 41 446
Frederick M. Waltz 223 0.7× 22 0.3× 29 0.4× 20 0.5× 30 0.9× 54 394
Tianxiang Bai 294 1.0× 24 0.3× 26 0.4× 31 0.8× 18 0.5× 27 422
Weize Quan 305 1.0× 27 0.3× 29 0.4× 13 0.4× 28 0.8× 22 379
Meng Yu 120 0.4× 53 0.7× 25 0.4× 10 0.3× 16 0.5× 45 416

Countries citing papers authored by Shi-Nine Yang

Since Specialization
Citations

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

Fields of papers citing papers by Shi-Nine Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shi-Nine Yang. 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 Shi-Nine Yang. The network helps show where Shi-Nine Yang may publish in the future.

Co-authorship network of co-authors of Shi-Nine Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Shi-Nine Yang. A scholar is included among the top collaborators of Shi-Nine Yang 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 Shi-Nine Yang. Shi-Nine Yang 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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