Xinde Li

3.6k total citations
200 papers, 2.3k citations indexed

About

Xinde Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Xinde Li has authored 200 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Computer Vision and Pattern Recognition, 43 papers in Artificial Intelligence and 37 papers in Aerospace Engineering. Recurrent topics in Xinde Li's work include Gout, Hyperuricemia, Uric Acid (29 papers), Robotics and Sensor-Based Localization (25 papers) and Robotic Path Planning Algorithms (22 papers). Xinde Li is often cited by papers focused on Gout, Hyperuricemia, Uric Acid (29 papers), Robotics and Sensor-Based Localization (25 papers) and Robotic Path Planning Algorithms (22 papers). Xinde Li collaborates with scholars based in China, United States and Singapore. Xinde Li's co-authors include Mohammad Omar Khyam, Shuzhi Sam Ge, Jean Dezert, Chaomin Luo, Xianghui Li, Changgui Li, Zain Anwar Ali, Mark R. Pickering, Md. Noor‐A‐Rahim and Simon X. Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Diabetes.

In The Last Decade

Xinde Li

173 papers receiving 2.2k citations

Author Peers

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

Author Last Decade Papers Cites
Xinde Li 641 337 329 324 310 200 2.3k
Haibo Zhang 343 0.5× 213 0.6× 32 0.1× 207 0.6× 517 1.7× 273 2.7k
Jun Gao 892 1.4× 37 0.1× 166 0.5× 100 0.3× 222 0.7× 122 2.3k
Rıfat Hacıoğlu 175 0.3× 146 0.4× 64 0.2× 479 1.5× 148 0.5× 44 1.4k
Weibing Li 488 0.8× 262 0.8× 17 0.1× 1.3k 3.9× 688 2.2× 185 3.8k
Domenico Grimaldi 195 0.3× 177 0.5× 21 0.1× 212 0.7× 313 1.0× 176 2.4k
Ning Li 67 0.1× 340 1.0× 49 0.1× 749 2.3× 336 1.1× 261 2.8k
Zhiyu Huang 468 0.7× 61 0.2× 20 0.1× 566 1.7× 390 1.3× 77 2.4k
Jiankun Wang 1.4k 2.1× 182 0.5× 10 0.0× 553 1.7× 223 0.7× 168 2.4k
Xiaoguang Hu 463 0.7× 157 0.5× 12 0.0× 378 1.2× 165 0.5× 175 1.6k
Yunzhou Zhang 669 1.0× 113 0.3× 11 0.0× 194 0.6× 229 0.7× 255 2.6k

Countries citing papers authored by Xinde Li

Since Specialization
Citations

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

Fields of papers citing papers by Xinde Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xinde Li

This figure shows the co-authorship network connecting the top 25 collaborators of Xinde Li. A scholar is included among the top collaborators of Xinde Li 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 Xinde Li. Xinde Li 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.
Cui, Lingling, Robert Terkeltaub, Xinde Li, et al.. (2025). Risk of Hepatotoxicity in Patients With Gout Treated With Febuxostat or Benzbromarone: A Propensity Score–Matched Cohort Study. Arthritis Care & Research. 77(9). 1149–1156. 2 indexed citations
2.
Li, Xinde, et al.. (2025). Certainty From Uncertainty: Multigranularity Labeling Inspired by Quantum Collapse for Learning With Noisy Labels in Fault Diagnosis. IEEE Transactions on Industrial Informatics. 21(8). 6443–6454. 2 indexed citations
3.
Peng, Hao, Huaping Liu, Xiang Li, et al.. (2025). What foundation models can bring for robot learning in manipulation: A survey. The International Journal of Robotics Research.
4.
Li, Xinde, et al.. (2024). The smallest endohedral borafullerene: structural isomerization, electronic properties, aromaticity and reactivity of U@C27B. Inorganic Chemistry Frontiers. 11(9). 2735–2751. 9 indexed citations
5.
Sun, Mingshu, Robert Terkeltaub, Tony R. Merriman, et al.. (2024). Hyperuricemia Subtypes Classified According to Renal Uric Acid Handling Manifesting Distinct Phenotypic and Genetic Profiles in People With Gout. Arthritis & Rheumatology. 76(7). 1130–1140. 5 indexed citations
6.
Li, Xinde, et al.. (2024). Like draws to like: A Multi-granularity Ball-Intra Fusion approach for fault diagnosis models to resists misleading by noisy labels. Advanced Engineering Informatics. 60. 102425–102425. 23 indexed citations
7.
Zhou, Ri‐Gui, et al.. (2024). A novel multi-criteria conflict evidence combination method and its application to pattern recognition. Information Fusion. 108. 102346–102346. 3 indexed citations
8.
Hu, Chuanfei, Tianyi Xia, Yuancheng Wang, et al.. (2024). Trustworthy multi-phase liver tumor segmentation via evidence-based uncertainty. Engineering Applications of Artificial Intelligence. 133. 108289–108289. 30 indexed citations
9.
Li, Xinde, et al.. (2024). Evidence combination with multi-granularity belief structure for pattern classification. Information Sciences. 690. 121577–121577. 2 indexed citations
10.
Li, Heqing, et al.. (2024). Adaptive multi-granularity trust management scheme for UAV visual sensor security under adversarial attacks. Computers & Security. 148. 104108–104108. 3 indexed citations
11.
Li, Xinde, et al.. (2024). MgCNL: A Sample Separation Approach via Multi-Granularity Balls for Fault Diagnosis With the Interference of Noisy Labels. IEEE Transactions on Automation Science and Engineering. 22. 7748–7761. 7 indexed citations
12.
Zhang, Ya, et al.. (2024). Regional Multi-Agent Cooperative Reinforcement Learning for City-Level Traffic Grid Signal Control. IEEE/CAA Journal of Automatica Sinica. 11(9). 1987–1998. 7 indexed citations
13.
Li, Heqing, et al.. (2024). Trust Measurement of Visual Data Based on Multigranularity Belief Fusion for UAV Perception System. IEEE Transactions on Instrumentation and Measurement. 73. 1–13. 1 indexed citations
14.
Li, Xinde, et al.. (2023). A two-branch deep learning with spatial and pose constraints for social group detection. Engineering Applications of Artificial Intelligence. 124. 106583–106583.
15.
Li, Xinde, et al.. (2023). Graph-Structure-Based Multigranular Belief Fusion for Human Activity Recognition. IEEE Transactions on Neural Networks and Learning Systems. 35(10). 13589–13603. 6 indexed citations
16.
Li, Xinde, et al.. (2021). Multi-Criteria Analysis of Sensor Reliability for Wearable Human Activity Recognition. IEEE Sensors Journal. 21(17). 19144–19156. 5 indexed citations
17.
Li, Xianghui, et al.. (2021). Robust Vehicle Detection in High-Resolution Aerial Images With Imbalanced Data. IEEE Transactions on Artificial Intelligence. 2(3). 238–250. 26 indexed citations
18.
Peng, Gang, et al.. (2021). Robust Tightly Coupled Pose Measurement Based on Multi-Sensor Fusion in Mobile Robot System. Sensors. 21(16). 5522–5522. 4 indexed citations
19.
Li, Junjun, Zhijun Li, Xinde Li, et al.. (2020). Skill Learning Strategy Based on Dynamic Motion Primitives for Human–Robot Cooperative Manipulation. IEEE Transactions on Cognitive and Developmental Systems. 13(1). 105–117. 45 indexed citations
20.
Li, Xinde, et al.. (2019). A Novel Multi-Criteria Discounting Combination Approach for Multi-Sensor Fusion. IEEE Sensors Journal. 19(20). 9411–9421. 5 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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