Feilong Chen

1.5k total citations · 1 hit paper
53 papers, 994 citations indexed

About

Feilong Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Industrial and Manufacturing Engineering. According to data from OpenAlex, Feilong Chen has authored 53 papers receiving a total of 994 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 7 papers in Industrial and Manufacturing Engineering. Recurrent topics in Feilong Chen's work include Multimodal Machine Learning Applications (7 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Industrial Vision Systems and Defect Detection (6 papers). Feilong Chen is often cited by papers focused on Multimodal Machine Learning Applications (7 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Industrial Vision Systems and Defect Detection (6 papers). Feilong Chen collaborates with scholars based in China, Taiwan and United States. Feilong Chen's co-authors include Xiuyi Chen, Duzhen Zhang, Shuang Xu, Young‐Joon Seo, Saeyeon Roh, Bo Xu, Jing Shi, Pang‐Ning Tan, Fandong Meng and Jie Zhou and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and International Journal of Production Research.

In The Last Decade

Feilong Chen

49 papers receiving 928 citations

Hit Papers

VLP: A Survey on Vision-language Pre-training 2023 2026 2024 2025 2023 25 50 75 100
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.

  1. VLP: A Survey on Vision-language Pre-training
    2023 118 citations Feilong Chen, Duzhen Zhang et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Feilong Chen China 16 386 241 238 129 108 53 994
Chaoqun Li China 25 1.4k 3.7× 131 0.5× 352 1.5× 113 0.9× 28 0.3× 72 2.0k
Somnath Mukhopadhyay India 15 172 0.4× 42 0.2× 126 0.5× 79 0.6× 26 0.2× 66 810
Ekrem Duman Türkiye 16 930 2.4× 285 1.2× 101 0.4× 172 1.3× 410 3.8× 42 1.4k
Jee-Hyong Lee South Korea 16 383 1.0× 134 0.6× 187 0.8× 183 1.4× 9 0.1× 145 1.1k
Víctor M. Rivas Spain 10 1.2k 3.2× 39 0.2× 183 0.8× 145 1.1× 26 0.2× 23 1.6k
Sergio Ramírez‐Gallego Spain 16 933 2.4× 39 0.2× 216 0.9× 103 0.8× 21 0.2× 21 1.7k
Carlos Castro Chile 14 403 1.0× 276 1.1× 65 0.3× 70 0.5× 18 0.2× 72 927

Countries citing papers authored by Feilong Chen

Since Specialization
Citations

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

Fields of papers citing papers by Feilong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feilong Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Feilong Chen. A scholar is included among the top collaborators of Feilong 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 Feilong Chen. Feilong 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.
Yang, Dong, et al.. (2025). A machine learning model integrating spatiotemporal attention and residual learning for predicting periodic air pollutant concentrations. Environmental Modelling & Software. 188. 106438–106438. 1 indexed citations
2.
3.
Cui, Cheng, Ling Qiu, Feilong Chen, et al.. (2024). A time series algorithm to predict surgery in neonatal necrotizing enterocolitis. BMC Medical Informatics and Decision Making. 24(1). 304–304. 2 indexed citations
4.
5.
Zhang, Duzhen, et al.. (2023). Decomposing Logits Distillation for Incremental Named Entity Recognition. 1919–1923. 10 indexed citations
6.
Zhang, Duzhen, Feilong Chen, Jianlong Chang, Xiuyi Chen, & Qi Tian. (2023). Structure Aware Multi-Graph Network for Multi-Modal Emotion Recognition in Conversations. IEEE Transactions on Multimedia. 26. 3987–3997. 9 indexed citations
7.
Zhang, Duzhen, Feilong Chen, & Xiuyi Chen. (2023). DualGATs: Dual Graph Attention Networks for Emotion Recognition in Conversations. 7395–7408. 23 indexed citations
8.
Chen, Feilong, et al.. (2023). VLP: A Survey on Vision-language Pre-training. arXiv (Cornell University). 20(1). 38–56. 118 indexed citations breakdown →
9.
Xiao, Jun, et al.. (2022). Complete Limits of Flow Network based on Critical Flow: Concept, Model, Algorithm, Visualization, and Applications. Arabian Journal for Science and Engineering. 48(1). 985–1007. 2 indexed citations
10.
Chen, Feilong, Fandong Meng, Xiuyi Chen, Peng Li, & Jie Zhou. (2021). Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation. 436–446. 11 indexed citations
11.
Chen, Feilong, Xiuyi Chen, Fandong Meng, Peng Li, & Jie Zhou. (2021). GoG: Relation-aware Graph-over-Graph Network for Visual Dialog. 17 indexed citations
12.
Chen, Xiuyi, Fandong Meng, Peng Li, et al.. (2020). Bridging the Gap between Prior and Posterior Knowledge Selection for Knowledge-Grounded Dialogue Generation. 3426–3437. 41 indexed citations
13.
Hao, Wenjun, Meng Yu, Jiaxing Lin, et al.. (2020). The pan-cancer landscape of netrin family reveals potential oncogenic biomarkers. Scientific Reports. 10(1). 5224–5224. 20 indexed citations
14.
Chen, Feilong. (2011). Analysis on the Verification of Older People's Handwriting. 1 indexed citations
15.
Chen, Feilong & Tsung-Yin Ou. (2011). CONSTRUCTING A SALES FORECASTING MODEL BY INTEGRATING GRA AND ELM:A CASE STUDY FOR RETAIL INDUSTRY. Int. J. Electron. Bus. Manag.. 9. 107–121. 6 indexed citations
16.
Huang, Ching-Chun & Feilong Chen. (2010). Economic Design of Max Charts. Communication in Statistics- Theory and Methods. 39(16). 2961–2976. 10 indexed citations
17.
Scripps, Jerry, Pang‐Ning Tan, Feilong Chen, & Abdol‐Hossein Esfahanian. (2009). A Matrix Alignment Approach for Collective Classification. 3. 155–159. 5 indexed citations
18.
Chen, Feilong & Rong Jin. (2007). Active algorithm selection. National Conference on Artificial Intelligence. 534–539. 1 indexed citations
19.
Chen, Feilong. (2007). On Structure and Link Mode of Cluster Supply Chain Network. Journal of Chengdu University of Technology. 1 indexed citations
20.
Chen, Feilong, et al.. (2004). Recognition of defect spatial patterns in semiconductor fabrication. International Journal of Production Research. 42(19). 4153–4172. 15 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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