Ning Yan

543 citations
18 papers · 349 · h-index 9

Impact in

    • Advanced Image Processing Techniques
    • Advanced Vision and Imaging
    • Advanced Data Compression Techniques
    • Advanced Image and Video Retrieval Techniques
    • Multimodal Machine Learning Applications
    • Image and Signal Denoising Methods
    • Human Pose and Action Recognition
    • Video Coding and Compression Technologies

Papers in

Ning Yan

17 papers receiving 342 citations

Peers

Ning Yan
Comparison fields: 5 of 41
  • Computer Vision and Pattern Recognition 309
  • Signal Processing 121
  • Artificial Intelligence 66
  • Media Technology 18
  • Computer Graphics and Computer-Aided Design 5
Replace Emre Aksu with:
Emre Aksu Finland
Troy Chinen United States
Dailan He China
Fatma Ezahra Sayadi Tunisia
Minyoung Kim South Korea
Myungsub Choi South Korea
Qunliang Xing China
Jeongin Seo South Korea
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Haitao Yang China
Ning Yan relative to Emre Aksu Finland Emre Aksu's profile →
Citations per field
00.5×7.9×
Emre Aksu · 1×
Citations per year

Countries citing papers authored by Ning Yan

Since Specialization
Citations

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

Fields of papers citing papers by Ning Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ning Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ning Yan Line = papers co-authored together Ning Yan links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201873
2 202170
3 202152
4 202146
5 201920
6 201919
7 201815
8 202014
9 202011
10 20206
11 20195
12 20235
13 20224
14 20203
15 20233
16 20202
17 20251
18 20250

About Ning Yan

Ning Yan is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Media Technology and Information Systems, having authored 18 papers that have together received 349 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (6 papers), Advanced Vision and Imaging (6 papers), Advanced Image Processing Techniques (6 papers), Advanced Data Compression Techniques (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Imbalanced Data Classification Techniques (2 papers), Image Processing Techniques and Applications (2 papers) and Food Quality and Safety Studies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (309 citations), Signal Processing (121 citations), Artificial Intelligence (66 citations), Media Technology (18 citations) and Computer Graphics and Computer-Aided Design (5 citations). Ning Yan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Houqiang Li, Dong Liu, Li Li, Feng Wu, Bir Bhanu, Bin Li, Kang Liu, Changsheng Gao, Zhu Li and Shan Liu. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Journal of Selected Topics in Signal Processing, ACM Transactions on Multimedia Computing Communications and Applications, Knowledge-Based Systems and Automation in Construction.

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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