Fanyang Meng

1.2k citations
57 papers · 657 indexed · h-index 13
Topics
Advanced Image Processing Techniques (12 papers)Image and Signal Denoising Methods (10 papers)Human Pose and Action Recognition (9 papers)

In The Last Decade

Fanyang Meng

45 papers receiving 640 citations

Peers

Fanyang Meng
Comparison fields: 5 of 93
  • Computer Vision and Pattern Recognition 327
  • Artificial Intelligence 297
  • Experimental and Cognitive Psychology 80
  • Biomedical Engineering 77
  • Signal Processing 76
Replace Akshay Vashist with:
Akshay Vashist United States
Mariana-Iuliana Georgescu Romania
Yunfan Liu China
Zhao-Min Chen China
Maheen Bakhtyar Pakistan
Awais Mahmood Saudi Arabia
Seong Tae Kim South Korea
Mannat Singh United States
Yao-Hung Hubert Tsai United States
Ben Fielding United Kingdom
Fanyang Meng relative to Akshay Vashist United States Akshay Vashist's profile →
Citations per field
00.5×7.1×
Akshay Vashist · 1×
Citations per year

Countries citing papers authored by Fanyang Meng

Since Specialization
Citations

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

Fields of papers citing papers by Fanyang Meng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fanyang Meng

This figure shows the co-authorship network connecting the top 25 collaborators of Fanyang Meng. A scholar is included among the top collaborators of Fanyang Meng 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 Fanyang Meng. Fanyang Meng 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 0
2 1
3 0
4 1
5 3
6 4
7 0
8 1
9 3
10 4
11 9
12 0
13 5
14 36
15 220
16 10
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About Fanyang Meng

Fanyang Meng is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Media Technology, having authored 57 papers that have together received 657 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (12 papers), Image and Signal Denoising Methods (10 papers) and Human Pose and Action Recognition (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (327 citations), Artificial Intelligence (297 citations) and Signal Processing (76 citations). Fanyang Meng has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Mengyuan Liu, Yongsheng Liang, Kai-Cheng Yang, Hua Xu, Yilin Zhu, Jiele Wu, Yixiao Ma, Wenmeng Yu, Hong Liu and Chen Chen. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and IEEE Transactions on Vehicular Technology.

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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