Yu Qin

453 citations
21 papers · 303 · h-index 9

Impact in

Papers in

Yu Qin

18 papers receiving 296 citations

Peers

Yu Qin
Comparison fields: 5 of 67
  • Instrumentation 39
  • Computer Vision and Pattern Recognition 113
  • Acoustics and Ultrasonics 2
  • Biophysics 12
  • Artificial Intelligence 66
Replace Hayato Wakabayashi with:
Hayato Wakabayashi Japan
Don‐Gey Liu Taiwan
Gilles Sicard France
Hongmei Li China
James A. Ratches United States
Andrew Burton United Kingdom
Seonghyeon Lee South Korea
Lin Gan China
José Manuel Rodríguez-Ramos Spain
Yajun Li China
Yu Qin relative to Hayato Wakabayashi Japan Hayato Wakabayashi's profile →
Citations per field
00.5×1.5×2.2×
Hayato Wakabayashi · 1×
Citations per year

Countries citing papers authored by Yu Qin

Since Specialization
Citations

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

Fields of papers citing papers by Yu Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201997
2 202140
3 202238
4 201635
5 201927
6 201818
7 202010
8 20198
9 20228
10 20196
11 20224
12 20243
13 20202
14 20222
15
Comparing Distance Metrics on Vectorized Persistence Summaries
20202
16
Improving the business performance of an SME in the UK through strategic quality management
20031
17 20101
18 20191
19 20250
20
The use of IT in life and health insurance product development
20200

About Yu Qin

Yu Qin is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Mechanical Engineering, Biomedical Engineering and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 303 indexed citations. Recurring topics across this work include Advanced machining processes and optimization (3 papers), Advanced MEMS and NEMS Technologies (3 papers), Advanced Machining and Optimization Techniques (3 papers), Advanced Surface Polishing Techniques (3 papers), Multimodal Machine Learning Applications (2 papers), Nonlinear Dynamics and Pattern Formation (2 papers), Neural Networks Stability and Synchronization (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Instrumentation (39 citations), Computer Vision and Pattern Recognition (113 citations), Acoustics and Ultrasonics (2 citations), Biophysics (12 citations) and Artificial Intelligence (66 citations). Yu Qin has collaborated with scholars based in China, Qatar and United Kingdom. Frequent co-authors include Jiajun Du, Yonghua Zhang, Hongtao Lu, Junjian Huang, Yongxiang Hu, Di Wu, Yu Zhou, Yan‐Jun Liu, Chao Zhang and Letian Wang. Their work appears in journals such as IEEE Access, Tsinghua Science & Technology, Journal of Bone and Mineral Research, Service Oriented Computing and Applications and Microsystem Technologies.

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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