Chen Tang

638 total citations
54 papers, 298 citations indexed

About

Chen Tang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Chen Tang has authored 54 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 19 papers in Artificial Intelligence and 9 papers in Electrical and Electronic Engineering. Recurrent topics in Chen Tang's work include Topic Modeling (11 papers), Advanced Neural Network Applications (7 papers) and Natural Language Processing Techniques (5 papers). Chen Tang is often cited by papers focused on Topic Modeling (11 papers), Advanced Neural Network Applications (7 papers) and Natural Language Processing Techniques (5 papers). Chen Tang collaborates with scholars based in China, United Kingdom and Singapore. Chen Tang's co-authors include Bin Zheng, Chenghua Lin, Heng-Yi Su, Xin Wang, Wei Wang, Frank Guérin, Xiao‐Wei Gao, Li Guo, Yongpan Liu and Hongbo Zhang and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Chen Tang

47 papers receiving 290 citations

Peers

Chen Tang
Alok Jain India
Mohsen Ali Pakistan
Cara MacNish Australia
Lu Zhou China
Nema Salem Saudi Arabia
Alok Jain India
Chen Tang
Citations per year, relative to Chen Tang Chen Tang (= 1×) peers Alok Jain

Countries citing papers authored by Chen Tang

Since Specialization
Citations

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

Fields of papers citing papers by Chen Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chen Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Chen Tang. A scholar is included among the top collaborators of Chen Tang 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 Chen Tang. Chen Tang 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
3.
Li, Ping, et al.. (2024). Bridging knowledge distillation gap for few-sample unsupervised semantic segmentation. Information Sciences. 673. 120714–120714. 5 indexed citations
5.
8.
Zhang, Yanjun, Bing Wang, Chen Tang, et al.. (2024). Enrichment and separation technology for evaluation of circulating tumor cells. Talanta. 282. 127025–127025. 6 indexed citations
9.
Tang, Chen, et al.. (2023). Student Engagement With Peer Feedback in L2 Writing: A Multiple Case Study of Chinese Secondary School Students. Chinese Journal of Applied Linguistics. 46(1). 120–139. 2 indexed citations
10.
Jiang, Hongyang, et al.. (2023). DCAMIL: Eye-tracking guided dual-cross-attention multi-instance learning for refining fundus disease detection. Expert Systems with Applications. 243. 122889–122889. 5 indexed citations
11.
Zhang, Nan, Mo Wang, Heng Xu, et al.. (2023). Reducing subgroup differences in personnel selection through the application of machine learning. Personnel Psychology. 76(4). 1125–1159. 18 indexed citations
12.
Tang, Chen, et al.. (2023). TwistList: Resources and Baselines for Tongue Twister Generation. 579–589. 3 indexed citations
13.
Tang, Chen, et al.. (2023). Enhancing Dialogue Generation via Dynamic Graph Knowledge Aggregation. 4604–4616. 9 indexed citations
14.
Tang, Chen, et al.. (2022). Social-aware Sparse Attention Network for Session-based Social Recommendation. 2173–2183. 4 indexed citations
15.
Su, Heng-Yi & Chen Tang. (2022). Dynamic-Error-Compensation-Assisted Deep Learning Framework for Solar Power Forecasting. IEEE Transactions on Sustainable Energy. 13(3). 1865–1868. 16 indexed citations
16.
Yue, Jinshan, Chen Tang, Yifan He, et al.. (2022). A Weight-Reload-Eliminated Compute-in-Memory Accelerator for 60 fps 4K Super-Resolution. IEEE Transactions on Circuits & Systems II Express Briefs. 70(3). 1179–1183. 3 indexed citations
17.
Wang, Wei, et al.. (2022). CAW: A Remote-Sensing Scene Classification Network Aided by Local Window Attention. Computational Intelligence and Neuroscience. 2022. 1–10. 1 indexed citations
18.
Tang, Chen, et al.. (2022). NGEP: A Graph-based Event Planning Framework for Story Generation. 186–193. 3 indexed citations
19.
Zhang, Leiying, et al.. (2022). Intrahepatic cholestasis of pregnancy can increase the risk of metabolic disorders: A meta-analysis. Journal of Medical Biochemistry. 41(4). 549–558. 7 indexed citations
20.
Zhou, Shuren, Chen Tang, & Jianping Yin. (2012). Research on pedestrian detection based on multi-detector fusion. Computer Engineering and Applications Journal. 48(23). 36–39. 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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