Suting Chen

1.3k total citations
89 papers, 1.0k citations indexed

About

Suting Chen is a scholar working on Computer Vision and Pattern Recognition, Infectious Diseases and Epidemiology. According to data from OpenAlex, Suting Chen has authored 89 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 24 papers in Infectious Diseases and 19 papers in Epidemiology. Recurrent topics in Suting Chen's work include Tuberculosis Research and Epidemiology (22 papers), Mycobacterium research and diagnosis (17 papers) and Advanced Image and Video Retrieval Techniques (9 papers). Suting Chen is often cited by papers focused on Tuberculosis Research and Epidemiology (22 papers), Mycobacterium research and diagnosis (17 papers) and Advanced Image and Video Retrieval Techniques (9 papers). Suting Chen collaborates with scholars based in China, Canada and Australia. Suting Chen's co-authors include Xiangdong Gao, Wenbing Yao, Hong Cai, Yan Sun, Jiayun Li, Song Chen, Hairong Huang, Rui Feng, Jin Meng and Ying Wang and has published in prestigious journals such as Nucleic Acids Research, The Journal of Immunology and PLoS ONE.

In The Last Decade

Suting Chen

84 papers receiving 994 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Suting Chen China 18 273 258 247 131 106 89 1.0k
Yunjin Lee South Korea 20 262 1.0× 409 1.6× 268 1.1× 416 3.2× 35 0.3× 74 1.8k
Mark Anderson United States 21 536 2.0× 363 1.4× 118 0.5× 202 1.5× 107 1.0× 53 1.8k
Wei‐Yao Wang Taiwan 21 463 1.7× 194 0.8× 84 0.3× 316 2.4× 49 0.5× 78 1.5k
Rong Bao China 21 281 1.0× 112 0.4× 214 0.9× 51 0.4× 90 0.8× 112 1.4k
Xiaoyu Feng China 23 530 1.9× 42 0.2× 180 0.7× 224 1.7× 139 1.3× 137 1.8k
Yanping Lu China 18 306 1.1× 187 0.7× 89 0.4× 18 0.1× 103 1.0× 76 1.0k
Akira Asano Japan 29 941 3.4× 83 0.3× 163 0.7× 297 2.3× 73 0.7× 150 2.4k
Aleksandra Tarkowska United Kingdom 8 1.3k 4.9× 165 0.6× 84 0.3× 30 0.2× 61 0.6× 9 2.0k
M. Wada Japan 17 596 2.2× 240 0.9× 307 1.2× 74 0.6× 57 0.5× 63 1.6k
Guillermo Ayala Spain 17 291 1.1× 48 0.2× 90 0.4× 257 2.0× 18 0.2× 79 1.1k

Countries citing papers authored by Suting Chen

Since Specialization
Citations

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

Fields of papers citing papers by Suting Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suting Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Suting Chen. A scholar is included among the top collaborators of Suting Chen 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 Suting Chen. Suting Chen 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.
Chen, Suting, et al.. (2025). GMFIMamba: Remote sensing change detection based on group Mamba feature interaction. Engineering Applications of Artificial Intelligence. 163. 112878–112878.
2.
Chen, Zhiwei & Suting Chen. (2024). Underwater target detection network based on differential routing assistance and bilateral attention synergy. Displays. 85. 102836–102836. 3 indexed citations
3.
Chen, Suting, et al.. (2024). Dual-branch deep cross-modal interaction network for semantic segmentation with thermal images. Engineering Applications of Artificial Intelligence. 135. 108820–108820. 2 indexed citations
4.
Liu, Huajun, et al.. (2024). Adaptive Fourier Convolution Network for Road Segmentation in Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–14. 7 indexed citations
5.
Wang, Hongjian & Suting Chen. (2024). DBMKA-Net:Dual branch multi-perception kernel adaptation for underwater image enhancement. Displays. 84. 102797–102797. 3 indexed citations
6.
Chen, Suting, et al.. (2024). A spatiotemporal motion prediction network based on multi-level feature disentanglement. Image and Vision Computing. 146. 105005–105005. 1 indexed citations
7.
Jiang, Haozhe, et al.. (2024). Exploring the Effects of Technology-Related Informal Mathematics Learning Activities: A Structural Equation Modeling Analysis. International Journal of Science and Mathematics Education. 23(1). 49–69. 6 indexed citations
8.
Chen, Suting, Fen Wang, Yi Xue, et al.. (2022). Doubled Nontuberculous Mycobacteria Isolation as a Consequence of Changes in the Diagnosis Algorithm. Infection and Drug Resistance. Volume 15. 3347–3355. 8 indexed citations
9.
Chen, Suting, Yao Liu, & Chuang Zhang. (2021). Water-Body Segmentation for Multi-Spectral Remote Sensing Images by Feature Pyramid Enhancement and Pixel Pair Matching. International Journal of Remote Sensing. 42(13). 5025–5043. 15 indexed citations
10.
Wang, Guirong, Guanglu Jiang, Wei Jing, et al.. (2021). Prevalence and molecular characterizations of seven additional drug resistance among multidrug-resistant tuberculosis in China: A subsequent study of a national survey. Journal of Infection. 82(3). 371–377. 22 indexed citations
11.
12.
Tang, Qian, Ying Wang, Xu Zheng, et al.. (2018). Evidence of metabolic memory-induced neurodegeneration and the therapeutic effects of glucagon-like peptide-1 receptor agonists via Forkhead box class O. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1865(2). 371–377. 15 indexed citations
13.
Yu, Xia, Guirong Wang, Suting Chen, et al.. (2016). Wild-Type and Non-Wild-Type Mycobacterium tuberculosis MIC Distributions for the Novel Fluoroquinolone Antofloxacin Compared with Those for Ofloxacin, Levofloxacin, and Moxifloxacin. Antimicrobial Agents and Chemotherapy. 60(9). 5232–5237. 18 indexed citations
14.
Liu, Yuan, Suting Chen, Bo‐Wen Pan, et al.. (2016). A subunit vaccine based on rH-NS induces protection against <italic>Mycobacterium tuberculosis</italic> infection by inducing the Th1 immune response and activating macrophages. Acta Biochimica et Biophysica Sinica. 48(10). 909–922. 2 indexed citations
15.
Chen, Suting, Yuanyuan Shang, Qian Liang, et al.. (2015). [Detection of mutations in the gyrA and gyrB genes associated with fluoroquinolone-resistance among clinical isolates of Mycobacterium abscessus in China].. PubMed. 38(7). 507–10. 1 indexed citations
16.
17.
Zhu, Lingxiang, Jun Zhong, Xinmiao Jia, et al.. (2015). Precision methylome characterization ofMycobacterium tuberculosiscomplex (MTBC) using PacBio single-molecule real-time (SMRT) technology. Nucleic Acids Research. 44(2). 730–743. 79 indexed citations
18.
Chen, Suting, Ming Qin, Yi Han, et al.. (2015). Assessment of the efficacy of drug transdermal delivery by electro-phonophoresis in treating tuberculous lymphadenitis. Drug Delivery. 23(5). 1588–1593. 11 indexed citations
19.
Chen, Suting, et al.. (2009). A Combined DNA Vaccine Provides Protective Immunity Against Mycobacterium bovis and Brucella abortus in Cattle. DNA and Cell Biology. 28(4). 191–199. 30 indexed citations
20.
Chen, Suting, et al.. (2009). Immunotherapy with combined DNA vaccines is an effective treatment for M. bovis infection in cattle. Vaccine. 27(9). 1317–1322. 9 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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