Jinyu Tian

107 total papers · 1.1k total citations
55 papers, 714 citations indexed

About

Jinyu Tian is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Jinyu Tian has authored 55 papers receiving a total of 714 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 19 papers in Artificial Intelligence and 9 papers in Electrical and Electronic Engineering. Recurrent topics in Jinyu Tian's work include Adversarial Robustness in Machine Learning (11 papers), Digital Media Forensic Detection (9 papers) and Anomaly Detection Techniques and Applications (6 papers). Jinyu Tian is often cited by papers focused on Adversarial Robustness in Machine Learning (11 papers), Digital Media Forensic Detection (9 papers) and Anomaly Detection Techniques and Applications (6 papers). Jinyu Tian collaborates with scholars based in China, Macao and India. Jinyu Tian's co-authors include Yuan Yan Tang, Jiantao Zhou, Anyong Qin, Zhaowei Shang, Taiping Zhang, Yulong Wang, Jun Liu, Haiwei Wu, Yuanman Li and Yu Qiao and has published in prestigious journals such as IEEE Transactions on Image Processing, Expert Systems with Applications and IEEE Journal on Selected Areas in Communications.

In The Last Decade

Jinyu Tian

46 papers receiving 696 citations

Hit Papers

Spectral–Spatial Graph Co... 2018 2026 2020 2023 2018 50 100 150 200 250

Author Peers

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

Author Last Decade Papers Cites
Jinyu Tian 335 330 193 116 46 55 714
Yanyan Xu 329 1.0× 305 0.9× 203 1.1× 176 1.5× 34 0.7× 40 812
Yanwen Chong 466 1.4× 334 1.0× 226 1.2× 94 0.8× 28 0.6× 54 897
Jiangbin Zheng 231 0.7× 248 0.8× 169 0.9× 138 1.2× 33 0.7× 24 735
Yongshan Zhang 350 1.0× 366 1.1× 410 2.1× 164 1.4× 61 1.3× 49 896
Badri Narayan Subudhi 560 1.7× 230 0.7× 159 0.8× 78 0.7× 35 0.8× 78 860
Hongwei Zhao 235 0.7× 202 0.6× 171 0.9× 95 0.8× 37 0.8× 73 759
Saqib Ali Nawaz 384 1.1× 115 0.3× 114 0.6× 46 0.4× 36 0.8× 36 825
Prudhvi Gurram 172 0.5× 173 0.5× 230 1.2× 99 0.9× 34 0.7× 48 667
Jinlong Yang 215 0.6× 237 0.7× 268 1.4× 93 0.8× 83 1.8× 70 664
Youqiang Zhang 203 0.6× 293 0.9× 147 0.8× 168 1.4× 142 3.1× 43 676

Countries citing papers authored by Jinyu Tian

Since Specialization
Citations

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

Fields of papers citing papers by Jinyu Tian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinyu Tian

This figure shows the co-authorship network connecting the top 25 collaborators of Jinyu Tian. A scholar is included among the top collaborators of Jinyu Tian 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 Jinyu Tian. Jinyu Tian 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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