Xiaohan Yu

2.4k citations
149 papers · 1.6k · h-index 22

Impact in

Papers in

Xiaohan Yu

136 papers receiving 1.6k citations

Peers

Xiaohan Yu
Comparison fields: 5 of 144
  • Condensed Matter Physics 425
  • Electronic, Optical and Magnetic Materials 583
  • Computer Vision and Pattern Recognition 364
  • Materials Chemistry 414
  • Radiation 67
Replace A. Scorzoni with:
A. Scorzoni Italy
Yimin Xiong China
Jinho Kim South Korea
Jicheng Wang China
Ziyuan Yang China
P. Bock United States
Xiaohan Yu relative to A. Scorzoni Italy A. Scorzoni's profile →
Citations per field
00.5×6.4×
A. Scorzoni · 1×
Citations per year

Countries citing papers authored by Xiaohan Yu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaohan Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 149 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201485
2 202260
3 202149
4 202144
5 201940
6 201232
7 202132
8 201931
9 202230
10 202029
11 201328
12 201928
13 200827
14 201927
15 201627
16 202027
17 202127
18 202325
19 202324
20 201924

About Xiaohan Yu

Xiaohan Yu is a scholar working on Computer Vision and Pattern Recognition, Electronic, Optical and Magnetic Materials, Condensed Matter Physics, Artificial Intelligence and Materials Chemistry, having authored 149 papers that have together received 1.6k indexed citations. Recurring topics across this work include Magnetic and transport properties of perovskites and related materials (38 papers), Advanced Condensed Matter Physics (28 papers), Domain Adaptation and Few-Shot Learning (17 papers), Multiferroics and related materials (16 papers), Video Surveillance and Tracking Methods (13 papers), Advanced Thermoelectric Materials and Devices (13 papers), Advanced Neural Network Applications (11 papers) and Advanced Image and Video Retrieval Techniques (10 papers). The work is most often cited by research in Condensed Matter Physics (425 citations), Electronic, Optical and Magnetic Materials (583 citations), Computer Vision and Pattern Recognition (364 citations), Materials Chemistry (414 citations) and Radiation (67 citations). Xiaohan Yu has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Yongsheng Gao, Xiang Liu, Yang Zhao, Shengwu Xiong, Shuaizhao Jin, Xiaoli Guan, Xin Gu, Xingrui Pu, Kaili Chu and Hongjiang Li. Their work appears in journals such as Ceramics International, Pattern Recognition, Journal of Alloys and Compounds, Applied Surface Science and Journal of Materials Science Materials in Electronics.

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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