Jingwen Ye

1.6k total citations · 1 hit paper
19 papers, 856 citations indexed

About

Jingwen Ye is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Jingwen Ye has authored 19 papers receiving a total of 856 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 2 papers in Control and Systems Engineering. Recurrent topics in Jingwen Ye's work include Advanced Neural Network Applications (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Jingwen Ye is often cited by papers focused on Advanced Neural Network Applications (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Jingwen Ye collaborates with scholars based in China, United States and Singapore. Jingwen Ye's co-authors include Mingli Song, Yongcheng Jing, Zunlei Feng, Yezhou Yang, Yizhou Yu, Xinchao Wang, Jie Song, Ying Chen, Zheng Li and Zhigeng Pan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Image Processing.

In The Last Decade

Jingwen Ye

16 papers receiving 835 citations

Hit Papers

Neural Style Transfer: A Review 2019 2026 2021 2023 2019 100 200 300 400
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. Neural Style Transfer: A Review
    2019 457 citations Yongcheng Jing, Yezhou Yang et al. IEEE Transactions on Visualization and Computer Graphics profile →

Peers

Jingwen Ye
Ning Xie China
Dongliang He China
Shuyang Gu China
Arsenii Ashukha Russia
Zhilong Zhang China
Hao Zhao China
Xiaoshan Yang China
Aleksander Holynski United States
Mike Zheng Shou Singapore
Xiaopeng Zhang China
Ning Xie China
Jingwen Ye
Citations per year, relative to Jingwen Ye Jingwen Ye (= 1×) peers Ning Xie

Countries citing papers authored by Jingwen Ye

Since Specialization
Citations

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

Fields of papers citing papers by Jingwen Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jingwen Ye

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

All Works

19 of 19 papers shown
1.
Wu, Yanqing, et al.. (2025). A deep-learning based method for accelerating dynamic reconfiguration of distribution networks. International Journal of Electrical Power & Energy Systems. 170. 110807–110807.
2.
Chen, Xiaoyun, et al.. (2023). Causal effect of gut microbiota on DNA methylation phenotypic age acceleration: a two-sample Mendelian randomization study. Scientific Reports. 13(1). 18830–18830. 5 indexed citations
3.
Liu, Songhua, et al.. (2023). Slimmable Dataset Condensation. 3759–3768. 26 indexed citations
4.
Ye, Jingwen, Songhua Liu, & Xinchao Wang. (2023). Partial Network Cloning. 20137–20146. 11 indexed citations
5.
Ye, Jingwen, Zunlei Feng, & Xinchao Wang. (2022). Flocking Birds of a Feather Together: Dual-step GAN Distillation via Realer-Fake Samples. 1–5.
6.
Song, Jie, Ying Chen, Jingwen Ye, & Mingli Song. (2022). Spot-Adaptive Knowledge Distillation. IEEE Transactions on Image Processing. 31. 3359–3370. 61 indexed citations
7.
Ye, Jingwen, et al.. (2022). Data Cleaning and AutoML: Would an Optimizer Choose to Clean?. Datenbank-Spektrum. 22(2). 121–130. 19 indexed citations
8.
Ye, Jingwen, et al.. (2022). Deep reinforcement learning based power system optimal carbon emission flow. Frontiers in Energy Research. 10. 5 indexed citations
9.
Guo, Peng, et al.. (2021). Study on Emission Reduction Strategies of Dual-Channel Supply Chain Considering Green Finance. Frontiers in Environmental Science. 9. 15 indexed citations
10.
Li, Zheng, et al.. (2021). Online Knowledge Distillation for Efficient Pose Estimation. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 11720–11730. 66 indexed citations
11.
Ye, Jingwen, et al.. (2020). Research on Evaluation of Safe Operation and Health State of Radar Power Supply System. SHILAP Revista de lepidopterología. 1 indexed citations
12.
Song, Jie, Yixin Chen, Jingwen Ye, et al.. (2020). DEPARA: Deep Attribution Graph for Deep Knowledge Transferability. 3921–3929. 13 indexed citations
13.
Ye, Jingwen, et al.. (2020). Data-Free Knowledge Amalgamation via Group-Stack Dual-GAN. 12513–12522. 33 indexed citations
14.
Ye, Jingwen, et al.. (2019). Amalgamating Filtered Knowledge: Learning Task-customized Student from Multi-task Teachers. 4128–4134. 17 indexed citations
15.
Ye, Jingwen, et al.. (2019). Edge-Sensitive Human Cutout With Hierarchical Granularity and Loopy Matting Guidance. IEEE Transactions on Image Processing. 29. 1177–1191. 9 indexed citations
16.
17.
Jing, Yongcheng, Yezhou Yang, Zunlei Feng, et al.. (2019). Neural Style Transfer: A Review. IEEE Transactions on Visualization and Computer Graphics. 26(11). 3365–3385. 457 indexed citations breakdown →
18.
Ye, Jingwen, Zunlei Feng, Yongcheng Jing, & Mingli Song. (2018). Finer-Net: Cascaded Human Parsing with Hierarchical Granularity. 1–6. 9 indexed citations
19.
Jing, Yongcheng, Yezhou Yang, Zunlei Feng, et al.. (2017). Neural Style Transfer: A Review. arXiv (Cornell University). 61 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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