Fangfang Wu
- Environmental Engineering top 1%
- Ecology top 2%
- Computer Vision and Pattern Recognition top 2%
- Plant Science top 5%
- Media Technology top 0.5%
- Topics
- Image and Signal Denoising Methods (15 papers)Remote Sensing and LiDAR Applications (12 papers)Advanced Image Fusion Techniques (10 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Geoscience and Remote SensingIEEE Transactions on Image Processing
- Partner nations
- ChinaUnited StatesCzechia
In The Last Decade
Fangfang Wu
50 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Environmental Engineering 858
- Ecology 652
- Computer Vision and Pattern Recognition 634
- Plant Science 572
- Media Technology 472
Countries citing papers authored by Fangfang Wu
This map shows the geographic impact of Fangfang Wu'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 Fangfang Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fangfang Wu more than expected).
Fields of papers citing papers by Fangfang Wu
This network shows the impact of papers produced by Fangfang Wu. 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 Fangfang Wu. The network helps show where Fangfang Wu may publish in the future.
Co-authorship network of co-authors of Fangfang Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Fangfang Wu. A scholar is included among the top collaborators of Fangfang Wu 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 Fangfang Wu. Fangfang Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 8 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 9 | |
| 8 | 13 | |
| 9 | 7 | |
| 10 | 7 | |
| 11 | 0 | |
| 12 | 171 | |
| 13 | 2 | |
| 14 | 3 | |
| 15 | 19 | |
| 16 | 101 | |
| 17 | 77 | |
| 18 | 114 | |
| 19 | Denoising Prior Driven Deep Neural Network for Image Restorationbreakdown → | 364 |
| 20 | 132 |
About Fangfang Wu
Fangfang Wu is a scholar working on Media Technology, Computer Vision and Pattern Recognition and General Engineering, having authored 58 papers that have together received 2.1k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (15 papers), Remote Sensing and LiDAR Applications (12 papers) and Advanced Image Fusion Techniques (10 papers). The work is most often cited by research in Environmental Engineering (858 citations), Media Technology (472 citations) and Computer Vision and Pattern Recognition (634 citations). Fangfang Wu has collaborated with scholars based in China, United States and Czechia. Frequent co-authors include Weisheng Dong, Guangming Shi, Qinghua Guo, Yanjun Su, Xiaotong Lu, Xin Li, Peiyao Wang, Wotao Yin, Shichao Jin and Shuxin Pang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.
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.