Shiding Sun

492 citations
29 papers · 341 · h-index 10

Impact in

Papers in

    • Advanced Neural Network Applications 6
    • Image Retrieval and Classification Techniques 3
    • Domain Adaptation and Few-Shot Learning 4
    • Text and Document Classification Technologies 4
    • Machine Learning and Data Classification 3
    • Machine Learning in Healthcare 2

Shiding Sun

25 papers receiving 337 citations

Peers

Shiding Sun
Comparison fields: 5 of 77
  • Hardware and Architecture 53
  • Computer Vision and Pattern Recognition 61
  • Artificial Intelligence 85
  • Mechanical Engineering 91
  • Health Informatics 3
Replace Jie Chu with:
Jie Chu China
Muhammad Umer Farooq Pakistan
Xiudong Li China
Huiming Chen China
Jinyang Li China
Alì Ibrahim Italy
Eugene Kim United States
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Shiding Sun relative to Jie Chu China Jie Chu's profile →
Citations per field
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Jie Chu · 1×
Citations per year

Countries citing papers authored by Shiding Sun

Since Specialization
Citations

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

Fields of papers citing papers by Shiding Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201964
2 201451
3 201939
4 201132
5 201923
6 202120
7 201819
8 202215
9 202313
10 20239
11 20239
12 20187
13 20247
14 20186
15 20225
16 20205
17 20214
18 20223
19 20223
20 20222

About Shiding Sun

Shiding Sun is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Mechanical Engineering and Media Technology, having authored 29 papers that have together received 341 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (6 papers), Domain Adaptation and Few-Shot Learning (4 papers), Text and Document Classification Technologies (4 papers), Software-Defined Networks and 5G (3 papers), Machine Learning and Data Classification (3 papers), Image Retrieval and Classification Techniques (3 papers), Cutaneous Melanoma Detection and Management (2 papers) and Machine Learning in Healthcare (2 papers). The work is most often cited by research in Hardware and Architecture (53 citations), Computer Vision and Pattern Recognition (61 citations), Artificial Intelligence (85 citations), Mechanical Engineering (91 citations) and Health Informatics (3 citations). Shiding Sun has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Guoyi Tang, Yanhong Ma, Jianguo Li, Yingjie Tian, Josiah Poon, Simon Poon, Akshay Wali, Akhil Dodda, Saptarshi Das and Şahin Kaya Özdemir. Their work appears in journals such as Pattern Recognition, Neural Networks, Artificial Intelligence in Medicine, Materials Science and Engineering A and British Journal of Dermatology.

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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