Xiaoran Chen

45 papers receiving 349 citations

Peers

Xiaoran Chen
Comparison fields: 5 of 109
  • Drug Discovery 1
  • Computer Vision and Pattern Recognition 91
  • Media Technology 39
  • Neurology 24
  • Artificial Intelligence 74
Replace Weihao Weng with:
Weihao Weng Japan
Hasan Al-Marzouqi United Arab Emirates
Ping Ma China
Abdul Rehman Khan Pakistan
Chen Cui China
Jinming Cao China
Nema Salem Saudi Arabia
Long Pang China
Xiaoran Chen relative to Weihao Weng Japan Weihao Weng's profile →
Citations per field
00.5×5.4×
Weihao Weng · 1×
Citations per year

Countries citing papers authored by Xiaoran Chen

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoran Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201856
2 202048
3 202034
4 202232
5 202421
6
Image enhancement effect on the performance of convolutional neural networks
201918
7 202114
8 202113
9 202311
10 201910
11 20219
12 20207
13 20146
14 20186
15 20206
16
The OOD Blind Spot of Unsupervised Anomaly Detection.
20215
17 20215
18 20195
19 20185
20 20224

About Xiaoran Chen

Xiaoran Chen is a scholar working on Computer Vision and Pattern Recognition, Mechanical Engineering, Artificial Intelligence, Civil and Structural Engineering and Control and Systems Engineering, having authored 54 papers that have together received 362 indexed citations. Recurring topics across this work include Geotechnical Engineering and Analysis (5 papers), Geotechnical Engineering and Soil Stabilization (4 papers), Adaptive Control of Nonlinear Systems (3 papers), Advanced Photocatalysis Techniques (3 papers), Optical measurement and interference techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Atmospheric chemistry and aerosols (3 papers) and Landslides and related hazards (3 papers). The work is most often cited by research in Drug Discovery (1 citation), Computer Vision and Pattern Recognition (91 citations), Media Technology (39 citations), Neurology (24 citations) and Artificial Intelligence (74 citations). Xiaoran Chen has collaborated with scholars based in China, Switzerland and Austria. Frequent co-authors include Ender Konukoglu, Sicong Li, Xin Liu, Yuhua Chen, Luc Van Gool, Jun Li, Wei Han, Lin Han, Wenwen Li and Feng Zhang. Their work appears in journals such as Applied Sciences, Agronomy, Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture, Journal of Environmental Management and IEEE Transactions on Geoscience and Remote Sensing.

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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