Yu Cheng

9.7k total citations · 3 hit papers
65 papers, 4.5k citations indexed

About

Yu Cheng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Yu Cheng has authored 65 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 26 papers in Computer Vision and Pattern Recognition and 8 papers in Control and Systems Engineering. Recurrent topics in Yu Cheng's work include Anomaly Detection Techniques and Applications (11 papers), Topic Modeling (8 papers) and Natural Language Processing Techniques (7 papers). Yu Cheng is often cited by papers focused on Anomaly Detection Techniques and Applications (11 papers), Topic Modeling (8 papers) and Natural Language Processing Techniques (7 papers). Yu Cheng collaborates with scholars based in United States, China and Japan. Yu Cheng's co-authors include Pan Zhou, Tao Zhang, Zhangyang Wang, Fang Chen, Xinyu Gong, Shuicheng Yan, Xiaohui Shen, Yifan Jiang, Ding Liu and Weining Lu and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Image Processing and IEEE Signal Processing Magazine.

In The Last Decade

Yu Cheng

63 papers receiving 4.3k citations

Hit Papers

align trajectories

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.

EnlightenGAN: Deep Light Enhancement Without Paired Supervision

2021 1.4k citations Yifan Jiang, Xinyu Gong et al. IEEE Transactions on Image Processing profile →
Deep Model Based Domain Adaptation for Fault Diagnosis

2016 612 citations Yu Cheng, Tao Zhang et al. profile →
Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges

2018 474 citations Yu Cheng, Duo Wang et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yu Cheng United States	23	2.4k	1.5k	763	604	388	65	4.5k
Nojun Kwak South Korea	29	2.3k 1.0×	1.9k 1.3×	279 0.4×	349 0.6×	183 0.5×	151	4.4k
Mingbo Zhao China	28	1.3k 0.5×	811 0.5×	550 0.7×	387 0.6×	346 0.9×	123	2.6k
Yiu‐ming Cheung Hong Kong	43	3.5k 1.5×	2.7k 1.8×	333 0.4×	704 1.2×	116 0.3×	362	6.8k
Yimin Yang China	30	870 0.4×	1.0k 0.7×	316 0.4×	143 0.2×	414 1.1×	149	3.1k
Xiao‐Jun Wu China	43	4.8k 2.0×	1.5k 1.0×	430 0.6×	3.0k 5.0×	206 0.5×	435	8.3k
Dong Huang China	38	2.7k 1.1×	2.2k 1.5×	259 0.3×	445 0.7×	120 0.3×	175	4.6k
Alexander G. Hauptmann United States	44	5.2k 2.2×	3.4k 2.3×	303 0.4×	665 1.1×	139 0.4×	149	8.0k
Guanqiu Qi United States	33	2.5k 1.0×	616 0.4×	600 0.8×	1.5k 2.4×	248 0.6×	124	4.5k
David B. Rosen United States	11	731 0.3×	2.1k 1.4×	429 0.6×	158 0.3×	106 0.3×	20	3.3k
Adam Coates United States	17	2.5k 1.0×	2.0k 1.4×	450 0.6×	507 0.8×	98 0.3×	27	4.4k

Countries citing papers authored by Yu Cheng

Since Specialization

Citations

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

Fields of papers citing papers by Yu Cheng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Cheng

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

He, Song, et al.. (2025). Early warning of cryptocurrency reversal risks via multi-source data. Finance research letters. 85. 107890–107890. 4 indexed citations

2.

Cheng, Yu, et al.. (2025). Design and Optimization of Financial Market Risk Monitoring System Based on Big Data Machine Learning. Procedia Computer Science. 262. 553–560.

3.

Tian, Jie, et al.. (2024). Mitigating Boundary Ambiguity and Inherent Bias for Text Classification in the Era of Large Language Models. 7841–7864. 1 indexed citations

4.

Fang, Xiang, Daizong Liu, Xiaoye Qu, et al.. (2024). Not All Inputs Are Valid: Towards Open-Set Video Moment Retrieval using Language. 28–37. 1 indexed citations

5.

Du, Mengnan, Subhabrata Mukherjee, Yu Cheng, et al.. (2023). Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding. 7 indexed citations

6.

Zheng, Qiang, et al.. (2023). HGM-cNet: Integrating hippocampal gray matter probability map into a cascaded deep learning framework improves hippocampus segmentation. European Journal of Radiology. 162. 110771–110771. 3 indexed citations

7.

Cheng, Yu, et al.. (2023). In-Context Learning Unlocked for Diffusion Models. 8542–8562.

8.

Cheng, Jun, et al.. (2022). Eddy Current Imaging of Fiber Textures in CFRP Composite Based on Spatial Frequency Domain De-aliasing Method. Journal of Mechanical Engineering. 58(4). 14–14. 1 indexed citations

9.

Chen, Xiaohan, Yu Cheng, Shuohang Wang, et al.. (2021). EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets. 2195–2207. 26 indexed citations

10.

Jiang, Yifan, Xinyu Gong, Ding Liu, et al.. (2021). EnlightenGAN: Deep Light Enhancement Without Paired Supervision. IEEE Transactions on Image Processing. 30. 2340–2349. 1366 indexed citations breakdown →

11.

Wang, Duo, Ming Li, C. Eduardo Corrales, et al.. (2021). A novel dual-network architecture for mixed-supervised medical image segmentation. Computerized Medical Imaging and Graphics. 89. 101841–101841. 9 indexed citations

12.

Wang, Duo, Ming Li, C. Eduardo Corrales, et al.. (2019). Mixed-Supervised Dual-Network for Medical Image Segmentation. Lecture notes in computer science. 11765. 192–200. 15 indexed citations

13.

Wang, Duo, Yu Cheng, Mo Yu, Xiaoxiao Guo, & Tao Zhang. (2019). A hybrid approach with optimization-based and metric-based meta-learner for few-shot learning. Neurocomputing. 349. 202–211. 51 indexed citations

14.

Luo, Yuan, Yu Cheng, Özlem Uzuner, Peter Szolovits, & Justin Starren. (2017). Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes. Journal of the American Medical Informatics Association. 25(1). 93–98. 61 indexed citations

15.

Li, Chunliang, Wei-Cheng Chang, Yu Cheng, Yiming Yang, & Barnabás Póczos. (2017). MMD GAN: Towards Deeper Understanding of Moment Matching Network. arXiv (Cornell University). 30. 2203–2213. 62 indexed citations

16.

Sun, Zhaonan, Ying Li, Soumya Ghosh, et al.. (2017). A Data-Driven Method for Generating Robust Symptom Onset Indicators in Disease Registry Data.. AMIA. 1 indexed citations

17.

Cheng, Yu, Felix X. Yu, Rogério Feris, et al.. (2015). Fast Neural Networks with Circulant Projections.. arXiv (Cornell University). 16 indexed citations

18.

Cheng, Yu, et al.. (2015). Robust dual control MPC with application to soft-landing control. 3862–3867. 6 indexed citations

19.

Cheng, Yu, Ankit Agrawal, Alok Choudhary, Huan Liu, & Tao Zhang. (2014). Social Role Identification via Dual Uncertainty Minimization Regularization. 7. 767–772. 4 indexed citations

20.

Cheng, Yu, Lisa M. Brown, Quanfu Fan, et al.. (2013). IBM-North western@Trecvid 2013: Surveillance event detection(SED). 2 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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