Shuhang Gu
- Computer Vision and Pattern Recognition top 0.1%
- Media Technology top 0.05%
- Computational Mechanics top 0.5%
- Biomedical Engineering top 5%
- Artificial Intelligence top 5%
- Co-authors
- Lei ZhangWangmeng ZuoXiangchu FengKai ZhangJianrui CaiDeyu MengQi XieRadu Timofte
- Topics
- Advanced Image Processing Techniques (29 papers)Image and Signal Denoising Methods (18 papers)Advanced Vision and Imaging (18 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingExpert Systems with Applications
- Partner nations
- ChinaHong KongSwitzerland
In The Last Decade
Shuhang Gu
53 papers receiving 6.7k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Computer Vision and Pattern Recognition 5.9k
- Media Technology 3.1k
- Computational Mechanics 1.3k
- Biomedical Engineering 609
- Artificial Intelligence 405
Countries citing papers authored by Shuhang Gu
This map shows the geographic impact of Shuhang Gu'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 Shuhang Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuhang Gu more than expected).
Fields of papers citing papers by Shuhang Gu
This network shows the impact of papers produced by Shuhang Gu. 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 Shuhang Gu. The network helps show where Shuhang Gu may publish in the future.
Co-authorship network of co-authors of Shuhang Gu
This figure shows the co-authorship network connecting the top 25 collaborators of Shuhang Gu. A scholar is included among the top collaborators of Shuhang Gu 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 Shuhang Gu. Shuhang Gu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | Efficient Image Enhancement With a Diffusion-Based Frequency Priorbreakdown → | 18 |
| 5 | 1 | |
| 6 | 7 | |
| 7 | 6 | |
| 8 | 8 | |
| 9 | 5 | |
| 10 | 12 | |
| 11 | 96 | |
| 12 | 54 | |
| 13 | 21 | |
| 14 | 6 | |
| 15 | Learning a Deep Single Image Contrast Enhancer from Multi-Exposure Imagesbreakdown → | 792 |
| 16 | 38 | |
| 17 | 235 | |
| 18 | Weighted Nuclear Norm Minimization with Application to Image Denoisingbreakdown → | 1521 |
| 19 | Projective dictionary pair learning for pattern classification | 224 |
| 20 | 5 |
About Shuhang Gu
Shuhang Gu is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Computational Mathematics, having authored 54 papers that have together received 6.8k indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (29 papers), Image and Signal Denoising Methods (18 papers) and Advanced Vision and Imaging (18 papers). The work is most often cited by research in Media Technology (3.1k citations), Computer Vision and Pattern Recognition (5.9k citations) and Computational Mathematics (120 citations). Shuhang Gu has collaborated with scholars based in China, Hong Kong and Switzerland. Frequent co-authors include Lei Zhang, Wangmeng Zuo, Xiangchu Feng, Kai Zhang, Jianrui Cai, Deyu Meng, Qi Xie, Radu Timofte, Luc Van Gool and David Zhang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Expert Systems with Applications.
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.