Fa Zhu

1.3k citations
53 papers · 856 · h-index 18

Impact in

Papers in

Fa Zhu

42 papers receiving 813 citations

Peers

Fa Zhu
Comparison fields: 5 of 94
  • Computer Vision and Pattern Recognition 264
  • Artificial Intelligence 368
  • Geology 45
  • Environmental Engineering 110
  • Media Technology 49
Replace Hongshan Yu with:
Hongshan Yu China
Cheng Tan China
Bo Mao China
Shangbing Gao China
John Williams Australia
Christos Kyrkou Cyprus
Jason Ford Australia
Frederick Tung Canada
Kris De Brabanter United States
Fa Zhu relative to Hongshan Yu China Hongshan Yu's profile →
Citations per field
00.5×1.5×2.1×
Hongshan Yu · 1×
Citations per year

Countries citing papers authored by Fa Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Fa Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021153
2 201666
3 200955
4 201353
5 201850
6 202136
7 202135
8 201734
9 201633
10 201832
11 202328
12 202328
13 202324
14 202223
15 201321
16 202420
17 201620
18 202419
19 202316
20 201814

About Fa Zhu

Fa Zhu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Control and Systems Engineering and Media Technology, having authored 53 papers that have together received 856 indexed citations. Recurring topics across this work include Face and Expression Recognition (16 papers), Anomaly Detection Techniques and Applications (9 papers), Advanced Algorithms and Applications (5 papers), Text and Document Classification Technologies (5 papers), Remote-Sensing Image Classification (4 papers), Remote Sensing in Agriculture (4 papers), Remote Sensing and LiDAR Applications (4 papers) and Machine Learning and ELM (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (264 citations), Artificial Intelligence (368 citations), Geology (45 citations), Environmental Engineering (110 citations) and Media Technology (49 citations). Fa Zhu has collaborated with scholars based in China, Saudi Arabia and Australia. Frequent co-authors include Ning Ye, Jian Yang, Junbin Gao, Sheng Xu, Xingchi Chen, Chunyan Xu, Tongming Yin, Guobao Li, Ning Ye and Xizhan Gao. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Consumer Electronics, Expert Systems with Applications, Neurocomputing and IEEE Transactions on Neural Networks and Learning Systems.

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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