Jun Lyu

686 citations
27 papers · 281 · h-index 9

Impact in

    • Advanced Image Fusion Techniques
    • Image Processing Techniques and Applications
    • Advanced Image Processing Techniques
    • Image and Signal Denoising Methods
    • Advanced Vision and Imaging
    • Advanced Neural Network Applications

Papers in

Jun Lyu

21 papers receiving 276 citations

Peers

Jun Lyu
Comparison fields: 5 of 57
  • Media Technology 83
  • Computer Vision and Pattern Recognition 159
  • Health Informatics 5
  • Radiology, Nuclear Medicine and Imaging 60
  • Neurology 20
Replace Ujwala Patil with:
Ujwala Patil India
Hüseyin Fırat Türkiye
Geet Sahu India
Qing Cai China
Hezheng Lin China
Teresa E. Alarcón Mexico
Huihui Dong China
Jiayin Kang China
Guowu Yuan China
C. Fernández‐Maloigne France
Jun Lyu relative to Ujwala Patil India Ujwala Patil's profile →
Citations per field
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Ujwala Patil · 1×
Citations per year

Countries citing papers authored by Jun Lyu

Since Specialization
Citations

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

Fields of papers citing papers by Jun Lyu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Lyu, 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 Jun Lyu Line = papers co-authored together Jun Lyu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202272
2 202340
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4 202327
5 202220
6 202318
7 202313
8 202410
9 20239
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11 20244
12 20244
13 20224
14 20244
15 20243
16 20222
17 20161
18 20231
19 20251
20 20251

About Jun Lyu

Jun Lyu is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Media Technology and Artificial Intelligence, having authored 27 papers that have together received 281 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (8 papers), Medical Imaging Techniques and Applications (5 papers), Advanced MRI Techniques and Applications (5 papers), Image and Signal Denoising Methods (4 papers), Advanced Vision and Imaging (4 papers), Advanced Image Fusion Techniques (3 papers), Advanced Neural Network Applications (3 papers) and Medical Imaging and Analysis (3 papers). The work is most often cited by research in Media Technology (83 citations), Computer Vision and Pattern Recognition (159 citations), Health Informatics (5 citations), Radiology, Nuclear Medicine and Imaging (60 citations) and Neurology (20 citations). Jun Lyu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Chengyan Wang, Qing Cai, Weibo Chen, David Zhang, Jing Qin, Qi Dou, Xuan Wang, Weiqing Yan, Jindong Zhao and Jindong Xu. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, Frontiers in Oncology, ACM Transactions on Multimedia Computing Communications and Applications, Medical Image Analysis and International journal of agricultural and biological engineering.

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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