Fu-En Yang

409 total citations
13 papers, 229 citations indexed

About

Fu-En Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Fu-En Yang has authored 13 papers receiving a total of 229 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 3 papers in Information Systems. Recurrent topics in Fu-En Yang's work include Domain Adaptation and Few-Shot Learning (6 papers), Multimodal Machine Learning Applications (5 papers) and Generative Adversarial Networks and Image Synthesis (4 papers). Fu-En Yang is often cited by papers focused on Domain Adaptation and Few-Shot Learning (6 papers), Multimodal Machine Learning Applications (5 papers) and Generative Adversarial Networks and Image Synthesis (4 papers). Fu-En Yang collaborates with scholars based in Taiwan and United States. Fu-En Yang's co-authors include Yu-Chiang Frank Wang, Yu-Jhe Li, Yen‐Cheng Liu, Yu-Ying Yeh, Xiaofei Du, Yen‐Ting Liu, Yuan‐Hao Lee, Shang‐Fu Chen, Cheng-Fu Yang and Chia-Ching Lin and has published in prestigious journals such as IEEE Transactions on Image Processing, International Journal of Computer Vision and 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

In The Last Decade

Fu-En Yang

12 papers receiving 226 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fu-En Yang Taiwan 9 188 78 40 32 11 13 229
Masayuki Mukunoki Japan 10 233 1.2× 35 0.4× 15 0.4× 102 3.2× 7 0.6× 38 279
Andreas Leibetseder Austria 10 205 1.1× 69 0.9× 12 0.3× 20 0.6× 2 0.2× 20 259
Romaric Audigier France 8 155 0.8× 80 1.0× 8 0.2× 14 0.4× 6 0.5× 22 188
Myungsub Choi South Korea 4 186 1.0× 36 0.5× 30 0.8× 7 0.2× 8 0.7× 6 233
Wendong Zhang China 6 128 0.7× 26 0.3× 8 0.2× 16 0.5× 11 1.0× 16 147
Yunlu Xu China 8 324 1.7× 187 2.4× 14 0.3× 27 0.8× 4 0.4× 13 376
Hanshu Yan Singapore 7 144 0.8× 104 1.3× 17 0.4× 11 0.3× 21 1.9× 11 235
Chen Shen China 6 288 1.5× 109 1.4× 31 0.8× 8 0.3× 2 0.2× 20 347

Countries citing papers authored by Fu-En Yang

Since Specialization
Citations

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

Fields of papers citing papers by Fu-En Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fu-En Yang. 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 Fu-En Yang. The network helps show where Fu-En Yang may publish in the future.

Co-authorship network of co-authors of Fu-En Yang

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

All Works

13 of 13 papers shown
1.
Yang, Fu-En, et al.. (2024). Language-Guided Transformer for Federated Multi-Label Classification. Proceedings of the AAAI Conference on Artificial Intelligence. 38(12). 13882–13890. 3 indexed citations
2.
Yang, Fu-En, Yuan‐Hao Lee, Chia-Ching Lin, & Yu-Chiang Frank Wang. (2023). Semantics-Guided Intra-Category Knowledge Transfer for Generalized Zero-Shot Learning. International Journal of Computer Vision. 131(6). 1331–1345. 12 indexed citations
3.
Yang, Fu-En, et al.. (2023). Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation. 19102–19111. 21 indexed citations
4.
Chang, Chih‐Jung, et al.. (2023). Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 2695–2704. 3 indexed citations
5.
Lee, Yuan‐Hao, Fu-En Yang, & Yu-Chiang Frank Wang. (2022). A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 1607–1617. 14 indexed citations
6.
Yang, Fu-En, et al.. (2021). Adversarial Teacher-Student Representation Learning for Domain Generalization. Neural Information Processing Systems. 34. 17 indexed citations
8.
Yang, Fu-En, et al.. (2021). Few-Shot Classification in Unseen Domains by Episodic Meta-Learning Across Visual Domains. 434–438. 1 indexed citations
9.
Yang, Cheng-Fu, et al.. (2021). LayoutTransformer: Scene Layout Generation with Conceptual and Spatial Diversity. 3731–3740. 25 indexed citations
10.
Yang, Fu-En, et al.. (2020). Learning Identity-Invariant Motion Representations for Cross-ID Face Reenactment. 7082–7090. 19 indexed citations
11.
Yang, Fu-En, et al.. (2019). A Multi-Domain and Multi-Modal Representation Disentangler for Cross-Domain Image Manipulation and Classification. IEEE Transactions on Image Processing. 29. 2795–2807. 8 indexed citations
12.
Liu, Yen‐Ting, Yu-Jhe Li, Fu-En Yang, Shang‐Fu Chen, & Yu-Chiang Frank Wang. (2019). Learning Hierarchical Self-Attention for Video Summarization. 3377–3381. 39 indexed citations
13.
Li, Yu-Jhe, Fu-En Yang, Yen‐Cheng Liu, et al.. (2018). Adaptation and Re-identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-identification. 67 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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