Kui Yang

521 citations
20 papers · 410 · h-index 8

Impact in

Papers in

Kui Yang

20 papers receiving 369 citations

Peers

Kui Yang
Comparison fields: 5 of 60
  • Acoustics and Ultrasonics 32
  • Computer Vision and Pattern Recognition 234
  • Media Technology 100
  • Instrumentation 19
  • Automotive Engineering 53
Replace Mohan Shankar with:
Mohan Shankar United States
Yi Pang China
Xudong Li China
Samia Aïnouz France
Fan Wang Japan
T. Takahashi Japan
Pirazh Khorramshahi United States
Hongzhi Jiang China
Kui Yang relative to Mohan Shankar United States Mohan Shankar's profile →
Citations per field
00.5×10×13.3×
Mohan Shankar · 1×
Citations per year

Countries citing papers authored by Kui Yang

Since Specialization
Citations

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

Fields of papers citing papers by Kui Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2018127
2 201980
3 201560
4 201749
5 201727
6 201319
7 201913
8 202212
9 20154
10 20213
11 20153
12 20172
13 20192
14 20242
15 20142
16
Studies on Seed Selection and Kinetic Model of Microorganism Enzymatic Steroid Transformation Using Computer Image Texture Analysis Technique
19941
17 20131
18
Application of Least Squares Support Vector Machine in Fault Diagnosis
20071
19 20231
20 20131

About Kui Yang

Kui Yang is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Control and Systems Engineering, Media Technology and Orthopedics and Sports Medicine, having authored 20 papers that have together received 410 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (7 papers), Image Enhancement Techniques (5 papers), Optical measurement and interference techniques (4 papers), Vehicle Dynamics and Control Systems (2 papers), Effects of Vibration on Health (2 papers), Optical Coherence Tomography Applications (2 papers), Advanced Image Fusion Techniques (2 papers) and Robotics and Sensor-Based Localization (1 paper). The work is most often cited by research in Acoustics and Ultrasonics (32 citations), Computer Vision and Pattern Recognition (234 citations), Media Technology (100 citations), Instrumentation (19 citations) and Automotive Engineering (53 citations). Kui Yang has collaborated with scholars based in China and Hong Kong. Frequent co-authors include Fei Liu, Pingli Han, Lu Bai, Xiaopeng Shao, Jin Xu, Xuan Li, Yiming Shao, Gongyuan Lu, Wei Yi and Zhang Guang. Their work appears in journals such as Optik, Photonics, Optics Letters, Chinese Optics Letters and Applied Optics.

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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