Liyang Chen

502 citations
20 papers · 241 · h-index 8

Impact in

Papers in

Liyang Chen

17 papers receiving 233 citations

Peers

Liyang Chen
Comparison fields: 5 of 58
  • Signal Processing 50
  • Computer Vision and Pattern Recognition 80
  • Artificial Intelligence 114
  • Industrial and Manufacturing Engineering 31
  • Instrumentation 9
Replace Marcin Piekarczyk with:
Marcin Piekarczyk Poland
Lantu Guo China
Haiming Yao China
Sungyong Baik South Korea
Jongheon Jeong South Korea
Quan Wang China
Sindy Löwe Netherlands
Ya Su China
Shaoxiang Chen China
Liyang Chen relative to Marcin Piekarczyk Poland Marcin Piekarczyk's profile →
Citations per field
00.5×3.9×
Marcin Piekarczyk · 1×
Citations per year

Countries citing papers authored by Liyang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Liyang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 202198
2 202129
3 202020
4 201619
5 202417
6 202310
7 202210
8 202210
9 20226
10 20236
11 20234
12 20234
13 20233
14 20182
15 20231
16
Use of Partial Cumulative Sum to Detect Trends and Change Periods for Nonlinear Time Series
20061
17 20241
18 20250
19 20250
20 20240

About Liyang Chen

Liyang Chen is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Control and Systems Engineering and Dermatology, having authored 20 papers that have together received 241 indexed citations. Recurring topics across this work include Speech and Audio Processing (6 papers), Speech Recognition and Synthesis (6 papers), Face recognition and analysis (5 papers), Human Motion and Animation (4 papers), Music and Audio Processing (4 papers), Topic Modeling (4 papers), Natural Language Processing Techniques (3 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). The work is most often cited by research in Signal Processing (50 citations), Computer Vision and Pattern Recognition (80 citations), Artificial Intelligence (114 citations), Industrial and Manufacturing Engineering (31 citations) and Instrumentation (9 citations). Liyang Chen has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Juntong Xi, Xinyi Le, Zhiyuan You, Nian Zhang, Yongquan Chen, Zhiyong Wu, Runnan Li, Yifeng Liu, Haiyong Xie and Wendong Xiao. Their work appears in journals such as Neurocomputing, IEEE Journal of Selected Topics in Signal Processing, Aesthetic Plastic Surgery, Archives of Dermatological Research and Complex & Intelligent Systems.

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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