Liangjun Chen

543 citations
21 papers · 298 · h-index 7

Impact in

Papers in

Liangjun Chen

20 papers receiving 297 citations

Peers

Liangjun Chen
Comparison fields: 5 of 66
  • Computer Vision and Pattern Recognition 70
  • Pediatrics, Perinatology and Child Health 54
  • Artificial Intelligence 99
  • Signal Processing 30
  • Radiology, Nuclear Medicine and Imaging 49
Replace Philip Chikontwe with:
Philip Chikontwe South Korea
Ashish Gupta India
Vamsi Krishna Ithapu United States
Beanbonyka Rim South Korea
S. N. Kumar India
Yunfei Liu China
Hassan Farsi Iran
Wutao Yin Canada
Xiang Wu China
Liangjun Chen relative to Philip Chikontwe South Korea Philip Chikontwe's profile →
Citations per field
00.5×3.8×
Philip Chikontwe · 1×
Citations per year

Countries citing papers authored by Liangjun Chen

Since Specialization
Citations

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

Fields of papers citing papers by Liangjun Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Liangjun 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 Liangjun Chen Line = papers co-authored together Liangjun Chen 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 201574
2 202362
3 201841
4 202229
5 201727
6 202112
7 202410
8 20236
9 20236
10 20215
11 20165
12 20234
13 20214
14 20233
15 20213
16 20233
17 20211
18 20231
19 20101
20 20211

About Liangjun Chen

Liangjun Chen is a scholar working on Pediatrics, Perinatology and Child Health, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 298 indexed citations. Recurring topics across this work include Neonatal and fetal brain pathology (8 papers), Fetal and Pediatric Neurological Disorders (7 papers), Functional Brain Connectivity Studies (6 papers), Advanced Neuroimaging Techniques and Applications (5 papers), Domain Adaptation and Few-Shot Learning (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Advanced Image Processing Techniques (2 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (70 citations), Pediatrics, Perinatology and Child Health (54 citations), Artificial Intelligence (99 citations), Signal Processing (30 citations) and Radiology, Nuclear Medicine and Imaging (49 citations). Liangjun Chen has collaborated with scholars based in China, United States and Norway. Frequent co-authors include Jihong Zhao, Hua Qu, Li Wang, Zhengwang Wu, Gang Li, Weili Lin, Badong Chen, José C. Prı́ncipe, Yue Sun and Paul Honeiné. Their work appears in journals such as NeuroImage, Nature Communications, Cell Reports, Nature Protocols and Neural Computing and Applications.

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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