Sheng Yu

480 total citations
30 papers, 284 citations indexed

About

Sheng Yu is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Human-Computer Interaction. According to data from OpenAlex, Sheng Yu has authored 30 papers receiving a total of 284 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Control and Systems Engineering, 10 papers in Computer Vision and Pattern Recognition and 9 papers in Human-Computer Interaction. Recurrent topics in Sheng Yu's work include Robot Manipulation and Learning (18 papers), Hand Gesture Recognition Systems (9 papers) and Human Pose and Action Recognition (5 papers). Sheng Yu is often cited by papers focused on Robot Manipulation and Learning (18 papers), Hand Gesture Recognition Systems (9 papers) and Human Pose and Action Recognition (5 papers). Sheng Yu collaborates with scholars based in China and Canada. Sheng Yu's co-authors include Yuanqing Xia, Di‐Hua Zhai, Haoran Wu, Jun Liao, Ling Peng, Jianying Chen, Said M. Easa, Yanqun Yang, Shulin Lü and Jinzhi Wang and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Access and Journal of Materials Science.

In The Last Decade

Sheng Yu

27 papers receiving 277 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sheng Yu China 9 178 92 81 59 52 30 284
Hongjie Fang China 7 193 1.1× 107 1.2× 83 1.0× 38 0.6× 57 1.1× 12 289
Yongxiang Fan United States 11 219 1.2× 86 0.9× 121 1.5× 30 0.5× 31 0.6× 23 266
Yuzhe Qin United States 10 252 1.4× 147 1.6× 109 1.3× 50 0.8× 82 1.6× 21 390
Riccardo Caccavale Italy 10 144 0.8× 60 0.7× 50 0.6× 21 0.4× 57 1.1× 23 247
Kuniyuki Takahashi Japan 10 107 0.6× 87 0.9× 70 0.9× 34 0.6× 44 0.8× 28 263
Marianna Madry Sweden 7 197 1.1× 81 0.9× 127 1.6× 29 0.5× 67 1.3× 12 283
Douglas Morrison Australia 4 266 1.5× 129 1.4× 153 1.9× 70 1.2× 85 1.6× 5 396
Huasong Min China 9 114 0.6× 88 1.0× 72 0.9× 20 0.3× 54 1.0× 53 272
Lee Chung Kwek Malaysia 8 164 0.9× 68 0.7× 115 1.4× 37 0.6× 67 1.3× 21 293
Claudia Pérez-D’Arpino United States 8 187 1.1× 165 1.8× 48 0.6× 35 0.6× 110 2.1× 14 370

Countries citing papers authored by Sheng Yu

Since Specialization
Citations

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

Fields of papers citing papers by Sheng Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheng Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Sheng Yu. A scholar is included among the top collaborators of Sheng 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 Sheng Yu. Sheng Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhai, Di‐Hua, et al.. (2025). SGNet: Robotic Suction Grasp Detection With Multiscale Attention. IEEE/ASME Transactions on Mechatronics. 30(6). 6927–6938. 2 indexed citations
2.
Yu, Sheng, et al.. (2025). Category-Level 6-D Object Pose Estimation With Learnable Prior Embeddings for Robotic Grasping. IEEE Transactions on Industrial Electronics. 72(11). 11682–11694. 1 indexed citations
3.
Yu, Sheng, Di‐Hua Zhai, & Yuanqing Xia. (2024). CatFormer: Category-Level 6D Object Pose Estimation with Transformer. Proceedings of the AAAI Conference on Artificial Intelligence. 38(7). 6808–6816. 5 indexed citations
4.
Yu, Sheng, Di‐Hua Zhai, & Yuanqing Xia. (2024). Synthetic Depth Image-Based Category-Level Object Pose Estimation With Effective Pose Decoupling and Shape Optimization. IEEE Transactions on Instrumentation and Measurement. 73. 1–18. 4 indexed citations
5.
Yu, Sheng, et al.. (2024). 6-D Object Pose Estimation Based on Point Pair Matching for Robotic Grasp Detection. IEEE Transactions on Neural Networks and Learning Systems. 36(7). 11902–11916. 1 indexed citations
6.
Guo, Wei, Sheng Yu, Jun Ding, et al.. (2024). Tailoring rejuvenation behavior of Zr-based metallic glass upon deep cryogenic cycling treatment. Transactions of Nonferrous Metals Society of China. 34(2). 582–591. 3 indexed citations
7.
Yu, Sheng, et al.. (2024). Robotic Grasp Detection With 6-D Pose Estimation Based on Graph Convolution and Refinement. IEEE Transactions on Systems Man and Cybernetics Systems. 54(6). 3783–3795. 5 indexed citations
8.
Yu, Sheng, Di‐Hua Zhai, & Yuanqing Xia. (2023). A Novel Robotic Pushing and Grasping Method Based on Vision Transformer and Convolution. IEEE Transactions on Neural Networks and Learning Systems. 35(8). 10832–10845. 16 indexed citations
9.
Yu, Sheng, et al.. (2023). Category-Level 6-D Object Pose Estimation With Shape Deformation for Robotic Grasp Detection. IEEE Transactions on Neural Networks and Learning Systems. 36(1). 1857–1871. 5 indexed citations
10.
Zhai, Di‐Hua, Sheng Yu, & Yuanqing Xia. (2023). FANet: Fast and Accurate Robotic Grasp Detection Based on Keypoints. IEEE Transactions on Automation Science and Engineering. 21(3). 2974–2986. 13 indexed citations
11.
Yu, Sheng, Di‐Hua Zhai, & Yuanqing Xia. (2023). Robotic Grasp Detection Based on Category-Level Object Pose Estimation With Self-Supervised Learning. IEEE/ASME Transactions on Mechatronics. 29(1). 625–635. 10 indexed citations
12.
Yu, Sheng, et al.. (2023). Thermo-fluid dynamics and morphology evolution of nickel-based superalloy in a multilayer laser directed energy deposition process. Journal of Materials Research and Technology. 28. 1276–1293. 6 indexed citations
13.
Peng, Ling, et al.. (2022). Research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanism. Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University. 40(2). 414–421. 3 indexed citations
14.
Yu, Sheng, Di‐Hua Zhai, & Yuanqing Xia. (2022). EGNet: Efficient Robotic Grasp Detection Network. IEEE Transactions on Industrial Electronics. 70(4). 4058–4067. 19 indexed citations
15.
Yu, Sheng, Di‐Hua Zhai, & Yuanqing Xia. (2022). CGNet: Robotic Grasp Detection in Heavily Cluttered Scenes. IEEE/ASME Transactions on Mechatronics. 28(2). 884–894. 19 indexed citations
16.
Yu, Sheng, et al.. (2021). A RGB-D based 6D Object Pose Estimation and Its Application in Robotic Grasping. 2021 China Automation Congress (CAC). 5953–5958.
17.
Peng, Ling, et al.. (2021). Detection of Surface Defects in Ceramic Tiles With Complex Texture. IEEE Access. 9. 92788–92797. 21 indexed citations
18.
Yang, Yanqun, et al.. (2020). Effectiveness of yellow color guardrail belt at freeway exits. Accident Analysis & Prevention. 146. 105737–105737. 9 indexed citations
19.
Yu, Sheng, et al.. (2018). Technical Development and Analysis of Four-wheel Aligner for Automobiles. 555–559. 1 indexed citations
20.
Wang, Fang, et al.. (2015). Magnetocaloric effect and critical behavior in Ni2In-type compound FeMn1−Ni Ge. Journal of Alloys and Compounds. 639. 259–262. 3 indexed citations

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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