Feng Wu

2.0k citations
74 papers · 1.3k indexed · 1 hit paper · h-index 16
Topics
Video Coding and Compression Technologies (17 papers)Advanced Data Compression Techniques (15 papers)Advanced Vision and Imaging (11 papers)

In The Last Decade

Feng Wu

64 papers receiving 1.3k citations

Hit Papers

Multi-Modality Cross Attention Network for Image and Sent...2020202620222024202050100150200250

Peers

Feng Wu
Comparison fields: 5 of 91
  • Computer Vision and Pattern Recognition 995
  • Signal Processing 416
  • Artificial Intelligence 287
  • Computer Networks and Communications 157
  • Electrical and Electronic Engineering 132
Replace Min Long with:
Min Long China
Anthony T. S. Ho United Kingdom
Charles Boncelet United States
Pengwei Hao United Kingdom
Olivier Déforges France
Debargha Mukherjee United States
Markus Flierl Sweden
T. Sikora Germany
Ioannis Katsavounidis United States
Yiannis Andreopoulos United Kingdom
Feng Wu relative to Min Long China Min Long's profile →
Citations per field
00.5×1.5×1.8×
Min Long · 1×
Citations per year

Countries citing papers authored by Feng Wu

Since Specialization
Citations

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

Fields of papers citing papers by Feng Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng Wu

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 0
3 1
4 3
5 13
6 1
7 17
8 180
9 4
10 5
11 17
12 10
13 2
14 2
15 3
16 1
17 25
18 17
19 4
20 7

About Feng Wu

Feng Wu is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology, having authored 74 papers that have together received 1.3k indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (17 papers), Advanced Data Compression Techniques (15 papers) and Advanced Vision and Imaging (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (995 citations), Signal Processing (416 citations) and Artificial Intelligence (287 citations). Feng Wu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Shipeng Li, Ya-Qin Zhang, Tianzhu Zhang, Xi Wei, Yan Li, Yongdong Zhang, Daqing Liu, Zheng-Jun Zha, Hanwang Zhang and Dong Liu. Their work appears in journals such as Nature Communications, IEEE Transactions on Image Processing and Optics Express.

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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