Tie Li

998 total citations · 1 hit paper
38 papers, 749 citations indexed

About

Tie Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Information Systems. According to data from OpenAlex, Tie Li has authored 38 papers receiving a total of 749 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 4 papers in Management Information Systems. Recurrent topics in Tie Li's work include Advanced Image and Video Retrieval Techniques (4 papers), Imbalanced Data Classification Techniques (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Tie Li is often cited by papers focused on Advanced Image and Video Retrieval Techniques (4 papers), Imbalanced Data Classification Techniques (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Tie Li collaborates with scholars based in China, United States and South Korea. Tie Li's co-authors include Yi Peng, Gang Kou, Philip S. Yu, Gui‐Peng Yang, Mao‐Xu Zhu, Weiwei Ma, Xiaoning Shi, Yanhong Li, Yongming Song and Guangxu Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and European Journal of Operational Research.

In The Last Decade

Tie Li

30 papers receiving 728 citations

Hit Papers

An Integrated Cluster Detection, Optimization, and Interp... 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. An Integrated Cluster Detection, Optimization, and Interpretation Approach for Financial Data
    2021 164 citations Tie Li, Gang Kou et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tie Li China 11 171 148 121 101 95 38 749
Tim Verdonck Belgium 16 295 1.7× 219 1.5× 120 1.0× 90 0.9× 161 1.7× 80 1.3k
Fei Hu China 18 250 1.5× 427 2.9× 67 0.6× 104 1.0× 86 0.9× 52 1.4k
Nonita Sharma India 16 307 1.8× 119 0.8× 47 0.4× 70 0.7× 153 1.6× 99 928
Xiaolei Li China 12 245 1.4× 94 0.6× 108 0.9× 139 1.4× 12 0.1× 63 842
Tzu‐Yu Lin Taiwan 11 248 1.5× 220 1.5× 72 0.6× 40 0.4× 152 1.6× 32 673
Kyong Joo Oh South Korea 20 207 1.2× 77 0.5× 346 2.9× 36 0.4× 563 5.9× 71 1.2k
Qiming Li China 18 82 0.5× 101 0.7× 154 1.3× 167 1.7× 370 3.9× 60 1.3k
Sheng-Tun Li Taiwan 21 527 3.1× 233 1.6× 200 1.7× 82 0.8× 450 4.7× 91 1.5k
Mohd Tahir Ismail Malaysia 13 88 0.5× 34 0.2× 223 1.8× 47 0.5× 219 2.3× 158 705
Yuval Cohen Israel 22 64 0.4× 89 0.6× 69 0.6× 37 0.4× 186 2.0× 94 1.9k

Countries citing papers authored by Tie Li

Since Specialization
Citations

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

Fields of papers citing papers by Tie Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tie Li

This figure shows the co-authorship network connecting the top 25 collaborators of Tie Li. A scholar is included among the top collaborators of Tie 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 Tie Li. Tie 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.
Li, Longfei, Tie Li, Yaoyao Qi, et al.. (2025). Laser Linewidth Measurement Using an FPGA-Based Delay Self-Homodyne System. Photonics. 12(3). 203–203.
2.
Liu, Zirui, et al.. (2025). Advances in Laser Linewidth Measurement Techniques: A Comprehensive Review. Micromachines. 16(9). 990–990. 1 indexed citations
3.
Li, Tie, et al.. (2025). Hyperspectral target detection based on graph sampling and aggregation network. PLoS ONE. 20(4). e0320043–e0320043.
4.
Gan, Yu, Xiaotong Zhang, Mao‐Xu Zhu, Tie Li, & Xiaoyan Cao. (2025). Experimental degradation of Ulva prolifera in sand sediments: Implications for dissolved carbon and alkalinity export from green-tide macroalgae buried in sandy intertidal zones. Marine Environmental Research. 209. 107216–107216.
5.
Li, Tie, Gang Kou, & Yi Peng. (2025). Learning user’s dynamic and personalized interests from E-commerce reviews of verified purchases: a time series based framework. Journal of the Operational Research Society. 76(12). 2464–2473. 1 indexed citations
6.
Li, Tie, et al.. (2024). An Intelligent Proofreading for Remote Skiing Actions Based on Variable Shape Basis. Mobile Networks and Applications. 3 indexed citations
7.
Hu, Qinglei, et al.. (2024). AFWS: Angle-Free Weakly Supervised Rotating Object Detection for Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–14. 6 indexed citations
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9.
Guo, Yangyang, Tie Li, Xiaoyan Cao, & Mao‐Xu Zhu. (2024). Effective capping of dissolved sulfide generated in Ulva prolifera-rich marine sediments by iron-rich red soil. Marine Pollution Bulletin. 203. 116424–116424. 1 indexed citations
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Li, Tie, et al.. (2023). An automatic fine-grained violence detection system for animation based on modified faster R-CNN. Expert Systems with Applications. 237. 121691–121691. 12 indexed citations
14.
Li, Tie, Gang Kou, & Yi Peng. (2023). A new representation learning approach for credit data analysis. Information Sciences. 627. 115–131. 8 indexed citations
15.
Li, Hongmin, Tie Li, Wei Feng, et al.. (2021). A novel image encryption scheme based on non-adjacent parallelable permutation and dynamic DNA-level two-way diffusion. Journal of Information Security and Applications. 61. 102844–102844. 33 indexed citations
16.
Li, Tie, Junyou Yang, & Cui Dai. (2020). Artificial-intelligence-based algorithms in multi-access edge computing for the performance optimization control of a benchmark microgrid. Physical Communication. 44. 101240–101240. 7 indexed citations
17.
Li, Tie, et al.. (2019). Overall calibration method of multibeam echo sounder installation biases based on terrain feature matching. SHILAP Revista de lepidopterología. 48(4). 512.
18.
Li, Tie, et al.. (2017). Classifying With Adaptive Hyper-Spheres: An Incremental Classifier Based on Competitive Learning. IEEE Transactions on Systems Man and Cybernetics Systems. 50(4). 1218–1229. 80 indexed citations
19.
Zhu, Mao‐Xu, et al.. (2012). Speciation and spatial distribution of solid-phase iron in surface sediments of the East China Sea continental shelf. Applied Geochemistry. 27(4). 892–905. 60 indexed citations
20.
Li, Tie. (2002). Advice the Development of the Real Estate and National Economy in China. 1 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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