Junwei Yang

815 citations
42 papers · 470 · 1 hit paper · h-index 10

Impact in

Papers in

Junwei Yang

36 papers receiving 462 citations

Junwei Yang's Hit Papers

A Comprehensive Survey on Deep Graph Representation Learning 2024 · 161 citations
1610+1Years since publication50100150

Peers

Junwei Yang
Comparison fields: 5 of 91
  • Artificial Intelligence 168
  • Computer Vision and Pattern Recognition 96
  • Signal Processing 46
  • Condensed Matter Physics 32
  • Radiology, Nuclear Medicine and Imaging 53
Replace K. Usha Rani with:
K. Usha Rani India
Liangmin Wang China
Xingyu Xie China
Kyungwoo Lee South Korea
Xiaohui Liu China
Yukun Huang China
Shan Ai China
Ye Lü China
Chengjian Sun China
Junwei Yang relative to K. Usha Rani India K. Usha Rani's profile →
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Countries citing papers authored by Junwei Yang

Since Specialization
Citations

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

Fields of papers citing papers by Junwei Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Comprehensive Survey on Deep Graph Representation Learning
Hit paper breakdown →
2024161
2 200469
3 202133
4 201632
5 200924
6 202116
7 202215
8 202213
9 202211
10 20239
11 20059
12 20167
13 20157
14 20086
15 20166
16 20246
17 20215
18 20254
19 20144
20 20223

About Junwei Yang

Junwei Yang is a scholar working on Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications, having authored 42 papers that have together received 470 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (8 papers), Medical Imaging Techniques and Applications (7 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Organic Electronics and Photovoltaics (3 papers), Organic Light-Emitting Diodes Research (3 papers), Cardiac Imaging and Diagnostics (3 papers), GaN-based semiconductor devices and materials (3 papers) and Speech Recognition and Synthesis (3 papers). The work is most often cited by research in Artificial Intelligence (168 citations), Computer Vision and Pattern Recognition (96 citations), Signal Processing (46 citations), Condensed Matter Physics (32 citations) and Radiology, Nuclear Medicine and Imaging (53 citations). Junwei Yang has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Wei Wang, Píetro Lió, Wei Ju, Ming Zhang, Yifang Qin, Ziyue Qiao, Qingqing Long, Zheng Fang, Yusheng Zhao and Jingyang Yuan. Their work appears in journals such as IEEE Transactions on Medical Imaging, Energy, Journal of Semiconductors, IEEE Transactions on Biomedical Engineering and Microelectronics Reliability.

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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