Xing An

425 total citations
22 papers, 239 citations indexed

About

Xing An is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biophysics. According to data from OpenAlex, Xing An has authored 22 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 4 papers in Biophysics. Recurrent topics in Xing An's work include Digital Imaging for Blood Diseases (4 papers), Cell Image Analysis Techniques (4 papers) and Image Processing Techniques and Applications (3 papers). Xing An is often cited by papers focused on Digital Imaging for Blood Diseases (4 papers), Cell Image Analysis Techniques (4 papers) and Image Processing Techniques and Applications (3 papers). Xing An collaborates with scholars based in China, United States and Japan. Xing An's co-authors include Di Lin, Jian Zhang, Ruijun Guo, Qian Zhou, Yusheng Ji, Celimuge Wu, Tsutomu Yoshinaga, Yalin Wang, Jie Shi and Marvin D. Nelson and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Electrochimica Acta.

In The Last Decade

Xing An

18 papers receiving 231 citations

Peers

Xing An
Marco Cascio Italy
Tomoko Tateyama Japan
Mihaela Gordan Romania
Kai Han China
Mingqi Gao China
Asit Kumar Subudhi India
Suane Pires P. da Silva Brazil
Hanxue Gu United States
Hüseyin Kutlu Türkiye
Linfeng Jiang China
Marco Cascio Italy
Xing An
Citations per year, relative to Xing An Xing An (= 1×) peers Marco Cascio

Countries citing papers authored by Xing An

Since Specialization
Citations

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

Fields of papers citing papers by Xing An

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xing An

This figure shows the co-authorship network connecting the top 25 collaborators of Xing An. A scholar is included among the top collaborators of Xing An 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 Xing An. Xing An 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
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Chen, Zhen‐Yu, Yali Wang, Xing An, et al.. (2024). CXCL13/CXCR5 axis facilitates TFH expansion and correlates with disease severity in adults with immune thrombocytopenia. Thrombosis Research. 244. 109196–109196. 2 indexed citations
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An, Xing, et al.. (2023). Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges. SHILAP Revista de lepidopterología. 4. 23–36. 48 indexed citations
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Zhang, Liangliang, et al.. (2022). The diagnostic effect of sensitive principal component method. Vibroengineering PROCEDIA. 42. 102–105. 1 indexed citations
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Zhuo, Zhiqing, et al.. (2020). Identifying the position of the compacted layer by measuring soil penetration resistance in a dryland farming region in Northeast China. Soil Use and Management. 36(3). 494–506. 12 indexed citations
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An, Xing, et al.. (2019). Application of Deep Learning in Quantitative Analysis of 2‐Dimensional Ultrasound Imaging of Nonalcoholic Fatty Liver Disease. Journal of Ultrasound in Medicine. 39(1). 51–59. 59 indexed citations
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Tang, Huang, et al.. (2017). リチウムイオン電池用の高性能アノード材料としてのマグネシウム熱反応による多孔質シリコン【Powered by NICT】. Electrochimica Acta. 228. 552. 1 indexed citations
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Li, Heng, Zhiwen Liu, Xing An, & Yonggang Shi. (2014). Multi-classification of cell deformation based on object alignment and run length statistic. PubMed. 2014. 3378–3381. 3 indexed citations
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Shi, Jie, Yalin Wang, Rafael Ceschin, et al.. (2013). A Multivariate Surface-Based Analysis of the Putamen in Premature Newborns: Regional Differences within the Ventral Striatum. PLoS ONE. 8(7). e66736–e66736. 30 indexed citations
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Huang, Yali, et al.. (2013). Quantitative Analysis of Lymphocytes Morphology and Motion in Intravital Microscopic Images. PubMed. 107. 3686–3689. 6 indexed citations
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Lin, Di, Xing An, & Jian Zhang. (2013). Double-bootstrapping source data selection for instance-based transfer learning. Pattern Recognition Letters. 34(11). 1279–1285. 37 indexed citations
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An, Xing, Zhiwen Liu, Yonggang Shi, et al.. (2012). Modeling Dynamic Cellular Morphology in Images. Lecture notes in computer science. 15(Pt 1). 340–347. 12 indexed citations
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Nandakumar, Vivek, Xing An, Yalin Wang, Roger H. Johnson, & Deirdre Meldrum. (2012). Conformal mapping of nuclei in 3D tomographic cell images to assess shape heterogeneity. 222–225. 4 indexed citations
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Shi, Jie, Yalin Wang, Rafael Ceschin, et al.. (2012). Surface fluid registration and multivariate tensor-based morphometry in newborns - the effects of prematurity on the putamen.. PubMed. 2012. 7 indexed citations
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An, Xing, Zhiwen Liu, Chuanfeng Lv, & Yonggang Shi. (2009). A Method of Quantitative Analysis for Dynamic Cellular Morphological Change. 105. 1–4.
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Lv, Chuanfeng, et al.. (2008). Lymphocyte Tracking and Shape Changing Analysis. 30. 118–122. 1 indexed citations
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Lv, Chuanfeng, et al.. (2008). Dual Weight Learning Vector Quantization. 1722–1725. 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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