Miao Fan

1.2k citations
35 papers · 598 indexed · h-index 14
Topics
Topic Modeling (14 papers)Advanced Image and Video Retrieval Techniques (9 papers)Advanced Graph Neural Networks (9 papers)
Partner nations
ChinaUnited StatesFrance

In The Last Decade

Miao Fan

34 papers receiving 580 citations

Peers

Miao Fan
Comparison fields: 5 of 70
  • Artificial Intelligence 408
  • Computer Vision and Pattern Recognition 188
  • Information Systems 132
  • Management Science and Operations Research 74
  • Transportation 42
Replace Chenyi Zhuang with:
Chenyi Zhuang Japan
Weidong Xiao China
Jinyang Gao China
Nicolas Usunier France
Xiaofei Zhou China
Xingzhong Du China
Mahmud Hasan Australia
Kyosuke Nishida Japan
Miao Fan relative to Chenyi Zhuang Japan Chenyi Zhuang's profile →
Citations per field
00.5×2.8×
Chenyi Zhuang · 1×
Citations per year

Countries citing papers authored by Miao Fan

Since Specialization
Citations

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

Fields of papers citing papers by Miao Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miao Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Miao Fan. A scholar is included among the top collaborators of Miao Fan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Miao Fan. Miao Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 6
3 16
4 89
5 9
6 1
7 2
8 32
9 8
10 5
11 20
12 17
13 7
14
Improving Event Detection with Active Learning
12
15
Table Region Detection on Large-scale PDF Files without Labeled Data.
7
16 1
17
Transition-based Knowledge Graph Embedding with Relational Mapping Properties
72
18
Bringing the Associative Ability to Social Tag Recommendation
2
19 1
20 2

About Miao Fan

Miao Fan is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 35 papers that have together received 598 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Advanced Graph Neural Networks (9 papers). The work is most often cited by research in Artificial Intelligence (408 citations), Computer Vision and Pattern Recognition (188 citations) and Transportation (42 citations). Miao Fan has collaborated with scholars based in China, United States and France. Frequent co-authors include Thomas Fang Zheng, Jizhou Huang, Mingming Sun, Qiang Zhou, Haifeng Wang, Ralph Grishman, Ping Li, Dongliang He, Fu Li and Min Yang. Their work appears in journals such as Remote Sensing, Pattern Recognition Letters and Speech Communication.

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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