Linhao Qu

794 citations
34 papers · 364 indexed · h-index 11

Impact in

Papers in

Linhao Qu

29 papers receiving 355 citations

Peers

Linhao Qu
Comparison fields: 5 of 64
  • Media Technology 168
  • Computer Vision and Pattern Recognition 199
  • Artificial Intelligence 109
  • Radiology, Nuclear Medicine and Imaging 77
  • Health Informatics 4
Replace Rajeshwar Dass with:
Rajeshwar Dass India
Tiep H. Vu United States
Sundaresh Ram United States
Anas M. Ali Saudi Arabia
Yuxuan Zheng China
Zohair Al‐Ameen Iraq
Dongsheng Jiang China
Yaning Feng China
Yuxin Fang China
Yawen Huang China
Linhao Qu relative to Rajeshwar Dass India Rajeshwar Dass's profile →
Citations per field
00.5×1.5×2.4×
Rajeshwar Dass · 1×
Citations per year

Countries citing papers authored by Linhao Qu

Since Specialization
Citations

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

Fields of papers citing papers by Linhao Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022112
2 202240
3 202227
4 202225
5 202218
6 202416
7 202315
8 202314
9 202313
10 202412
11 202310
12 20239
13 20248
14 20238
15 20236
16 20235
17 20235
18 20224
19 20243
20 20242

About Linhao Qu

Linhao Qu is a scholar working on Media Technology, Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Reproductive Medicine, having authored 34 papers that have together received 364 indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced Image Fusion Techniques (8 papers), Image Enhancement Techniques (7 papers), COVID-19 diagnosis using AI (5 papers), Domain Adaptation and Few-Shot Learning (5 papers), Advanced Neural Network Applications (4 papers) and Digital Imaging for Blood Diseases (4 papers). The work is most often cited by research in Media Technology (168 citations), Computer Vision and Pattern Recognition (199 citations), Artificial Intelligence (109 citations), Radiology, Nuclear Medicine and Imaging (77 citations) and Health Informatics (4 citations). Linhao Qu has collaborated with scholars based in China, Poland and France. Frequent co-authors include Manning Wang, Zhijian Song, Shaolei Liu, Zhijian Song, Siyu Liu, Xiaoyu Liu, Siqi Yin, Qinhao Guo, Qin Qiao and Haoran Wang. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Medical Imaging, Neural Computing and Applications and Scientific Reports.

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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