Shuyin Xia

2.9k total citations · 1 hit paper
107 papers, 1.8k citations indexed

About

Shuyin Xia is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Shuyin Xia has authored 107 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Artificial Intelligence, 50 papers in Computer Vision and Pattern Recognition and 26 papers in Computational Theory and Mathematics. Recurrent topics in Shuyin Xia's work include Face and Expression Recognition (24 papers), Rough Sets and Fuzzy Logic (24 papers) and Data Mining Algorithms and Applications (15 papers). Shuyin Xia is often cited by papers focused on Face and Expression Recognition (24 papers), Rough Sets and Fuzzy Logic (24 papers) and Data Mining Algorithms and Applications (15 papers). Shuyin Xia collaborates with scholars based in China, United States and Australia. Shuyin Xia's co-authors include Guoyin Wang, Zizhong Chen, Xinbo Gao, Elisabeth Giem, Qinghua Zhang, Hong Yu, Hao Zhang, Wenhua Li, Yunsheng Liu and Xin Ding and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Transactions on Image Processing.

In The Last Decade

Shuyin Xia

94 papers receiving 1.8k citations

Hit Papers

align trajectories

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.

3WC-GBNRS++: A Novel Three-Way Classifier With Granular-Ball Neighborhood Rough Sets Based on Uncertainty

2024 39 citations Jie Yang, Shuyin Xia et al. IEEE Transactions on Fuzzy Systems profile →

Peers

Shuyin Xia

AI

CVPR

CTM

IS

SP

Ayed Salman Kuwait

Jiucheng Xu China

Emrah Hançer Türkiye

Daniel Yeung Hong Kong

Sajjad Shaukat Jamal Saudi Arabia

Liang Bai China

B. John Oommen Canada

Jeremiah D. Deng New Zealand

Tianlong Gu China

Ayed Salman Kuwait

Shuyin Xia

1.2k ×1.0

AI

402 ×0.6

CVPR

412 ×0.7

CTM

216 ×0.7

IS

96 ×0.7

SP

Citations per year, relative to Shuyin Xia Shuyin Xia (= 1×) peers Ayed Salman

Countries citing papers authored by Shuyin Xia

Since Specialization

Citations

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

Fields of papers citing papers by Shuyin Xia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuyin Xia

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Huang, Fuxiang, et al.. (2025). Vision Mamba: A Comprehensive Survey and Taxonomy. IEEE Transactions on Neural Networks and Learning Systems. 37(2). 505–525. 8 indexed citations

2.

Li, Wentao, Lingwei Wei, Witold Pedrycz, et al.. (2025). Granular-Ball Regeneration Clustering With Principle of Justifiable Granularity. IEEE Transactions on Neural Networks and Learning Systems. 36(10). 18173–18187.

3.

Yang, Jie, et al.. (2025). CS3W-GBG: A Cost-Sensitive Three-Way Granular-Ball Generation Method. IEEE Transactions on Fuzzy Systems. 33(10). 3681–3694. 1 indexed citations

4.

Xia, Shuyin, et al.. (2025). FDSRM: A Feature-Driven Style-Agnostic Foundation Model for Sketch-Less Facial Image Retrieval. IEEE Transactions on Neural Networks and Learning Systems. PP. 1–15.

5.

Zhang, Qinghua, et al.. (2025). GAdaBoost: An efficient and robust AdaBoost algorithm based on granular-ball structure. Knowledge-Based Systems. 325. 113898–113898. 1 indexed citations

6.

Yang, Jie, Feng Lu, Guoyin Wang, et al.. (2025). Three-Way Outlier Detection Based on Shadowed Granular-Balls. IEEE Transactions on Fuzzy Systems. 34(1). 101–113.

7.

Xie, Jiang, et al.. (2025). AW-GBGAE: An Adaptive Weighted Graph Autoencoder Based on Granular-Balls for General Data Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(12). 11298–11314. 1 indexed citations

8.

Xia, Shuyin, et al.. (2024). Granular-Ball Fuzzy Set and Its Implement in SVM. IEEE Transactions on Knowledge and Data Engineering. 36(11). 6293–6304. 8 indexed citations

9.

Yang, Xin, et al.. (2024). Open Continual Feature Selection via Granular-Ball Knowledge Transfer. IEEE Transactions on Knowledge and Data Engineering. 36(12). 8967–8980. 4 indexed citations

10.

Zhang, Qinghua, et al.. (2024). GBG++: A Fast and Stable Granular Ball Generation Method for Classification. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(2). 2022–2036. 24 indexed citations

11.

Cheng, Dongdong, et al.. (2024). Granular-ball computing-based manifold clustering algorithms for ultra-scalable data. Expert Systems with Applications. 247. 123313–123313. 15 indexed citations

12.

Xie, Jiang, et al.. (2024). W-GBC: An Adaptive Weighted Clustering Method Based on Granular-Ball Structure. 914–925. 1 indexed citations

13.

Cheng, Dongdong, Ya Li, Shuyin Xia, et al.. (2023). A Fast Granular-Ball-Based Density Peaks Clustering Algorithm for Large-Scale Data. IEEE Transactions on Neural Networks and Learning Systems. 35(12). 17202–17215. 50 indexed citations

14.

Cheng, Dongdong, Jinlong Huang, Sulan Zhang, et al.. (2023). K-Means Clustering With Natural Density Peaks for Discovering Arbitrary-Shaped Clusters. IEEE Transactions on Neural Networks and Learning Systems. 35(8). 11077–11090. 41 indexed citations

15.

Zhang, Qinghua, Yunlong Cheng, Man Gao, et al.. (2023). Effective Value Analysis of Fuzzy Similarity Relation in HQSS for Efficient Granulation. IEEE Transactions on Neural Networks and Learning Systems. 35(9). 12849–12863. 4 indexed citations

16.

Zhao, Pengfei, Zizhong Chen, Jiang Xie, Shuyin Xia, & Guoyin Wang. (2023). A Novel Silhouettes Cluster Internal Evaluation Index Based on Granular-Ball. 20. 92–97. 1 indexed citations

17.

Xia, Tian, et al.. (2023). GBSMOTE: A Robust Sampling Method Based on Granular-ball Computing and SMOTE for Class Imbalance. 19–24. 2 indexed citations

18.

Xia, Shuyin, Guoyin Wang, Yunlong Cheng, et al.. (2022). An Efficient and Accurate Rough Set for Feature Selection, Classification, and Knowledge Representation. IEEE Transactions on Knowledge and Data Engineering. 35(8). 7724–7735. 39 indexed citations

19.

Wang, Chunjie, et al.. (2022). One-Stage Deep Edge Detection Based on Dense-Scale Feature Fusion and Pixel-Level Imbalance Learning. IEEE Transactions on Artificial Intelligence. 5(1). 70–79. 7 indexed citations

20.

Chen, Weiqi, Shuyin Xia, Cheng Wang, Zizhong Chen, & Guoyin Wang. (2022). GBCD: A Granular-ball Based Discretization Method for Continuous Valued Attributes. 10. 1340–1344.

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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