Xuanping Li

504 total citations · 1 hit paper
13 papers, 312 citations indexed

About

Xuanping Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Xuanping Li has authored 13 papers receiving a total of 312 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Cognitive Neuroscience. Recurrent topics in Xuanping Li's work include Advanced Image Fusion Techniques (3 papers), Medical Image Segmentation Techniques (3 papers) and EEG and Brain-Computer Interfaces (3 papers). Xuanping Li is often cited by papers focused on Advanced Image Fusion Techniques (3 papers), Medical Image Segmentation Techniques (3 papers) and EEG and Brain-Computer Interfaces (3 papers). Xuanping Li collaborates with scholars based in China, Singapore and United Kingdom. Xuanping Li's co-authors include Xue Wang, Yinwei Wei, Liqiang Nie, Qi Li, Xiang Wang, Tat‐Seng Chua, Yan Li, Weihang Zhang, Junfeng Chen and Pengbo Zhang and has published in prestigious journals such as IEEE Transactions on Image Processing, Computer Methods and Programs in Biomedicine and Measurement.

In The Last Decade

Xuanping Li

12 papers receiving 299 citations

Hit Papers

Contrastive Learning for Cold-Start Recommendation 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xuanping Li China 7 151 131 80 60 54 13 312
Abhijit S. Pandya United States 8 73 0.5× 103 0.8× 52 0.7× 33 0.6× 8 0.1× 62 322
Chien‐Chang Hsu Taiwan 10 70 0.5× 85 0.6× 84 1.1× 27 0.5× 13 0.2× 27 320
Muntasir Mamun United States 13 29 0.2× 212 1.6× 114 1.4× 147 2.5× 48 0.9× 17 463
G S Pradeep Ghantasala India 10 65 0.4× 126 1.0× 34 0.4× 25 0.4× 8 0.1× 63 322
Sirui Wang China 9 70 0.5× 388 3.0× 94 1.2× 55 0.9× 5 0.1× 40 547
Adina Crainiceanu United States 12 55 0.4× 74 0.6× 38 0.5× 43 0.7× 11 0.2× 26 434
Meshrif Alruily Saudi Arabia 12 62 0.4× 174 1.3× 57 0.7× 44 0.7× 8 0.1× 32 311
Sapiah Sakri Saudi Arabia 7 54 0.4× 205 1.6× 59 0.7× 50 0.8× 6 0.1× 16 374
Raed Alazaidah Jordan 14 123 0.8× 194 1.5× 60 0.8× 67 1.1× 24 0.4× 51 448
Jean-Christophe Burie France 13 34 0.2× 102 0.8× 300 3.8× 119 2.0× 90 1.7× 44 515

Countries citing papers authored by Xuanping Li

Since Specialization
Citations

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

Fields of papers citing papers by Xuanping Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xuanping Li

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

All Works

13 of 13 papers shown
1.
Zheng, Xi, et al.. (2025). Ray-Aided Quadruple Affiliation Network for Calculating Tumor-Stroma Ratios in Breast Cancers. IEEE Transactions on Image Processing. 34. 2811–2825.
2.
Wang, Xun, et al.. (2022). Modality-Balanced Embedding for Video Retrieval. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2578–2582. 3 indexed citations
3.
Wei, Yinwei, Xiang Wang, Qi Li, et al.. (2021). Contrastive Learning for Cold-Start Recommendation. 5382–5390. 165 indexed citations breakdown →
4.
Li, Xuanping, et al.. (2017). Adaptive Energy Weight Based Active Contour Model for Robust Medical Image Segmentation. Journal of Signal Processing Systems. 90(3). 449–465. 10 indexed citations
5.
Zhang, Weihang, Xue Wang, Xuanping Li, & Junfeng Chen. (2017). 3D skeletonization feature based computer-aided detection system for pulmonary nodules in CT datasets. Computers in Biology and Medicine. 92. 64–72. 46 indexed citations
6.
7.
Zhang, Pengbo, Xue Wang, Xuanping Li, & Peng Dai. (2016). EEG feature selection based on weighted-normalized mutual information for mental fatigue classification. 37. 1–6. 9 indexed citations
8.
9.
Li, Xuanping, et al.. (2015). Supervised recursive segmentation of volumetric CT images for 3D reconstruction of lung and vessel tree. Computer Methods and Programs in Biomedicine. 122(3). 316–329. 22 indexed citations
10.
Wang, Xue, et al.. (2015). Sparse EEG compressive sensing for web-enabled person identification. Measurement. 74. 11–20. 39 indexed citations
11.
Li, Xuanping, et al.. (2014). Robust global minimization of active contour model for multi-object medical image segmentation. 67. 1443–1448. 3 indexed citations
12.
Wang, Xue, et al.. (2014). Self-adaptive morphable model based multi-view non-cooperative 3D face reconstruction. 116. 320–325. 1 indexed citations
13.
Yang, Xiaoyan, et al.. (2006). Application study on public key cryptography in mobile payment. 97–102. 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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