Junfei Zhuang

1.9k citations
5 papers · 178 indexed · h-index 4
Topics
Video Surveillance and Tracking Methods (4 papers)Image Enhancement Techniques (3 papers)Fire Detection and Safety Systems (2 papers)
Journals
IEEE AccessNeurocomputingAsian Conference on Machine Learning
Partner nations
ChinaJapan

In The Last Decade

Junfei Zhuang

5 papers receiving 172 citations

Peers

Junfei Zhuang
Comparison fields: 5 of 50
  • Computer Vision and Pattern Recognition 110
  • Control and Systems Engineering 43
  • Aerospace Engineering 43
  • Safety, Risk, Reliability and Quality 33
  • Mechanical Engineering 27
Replace Zikai Song with:
Zikai Song China
Wilbert G. Aguilar Spain
Yangliu Kuai China
Qinghao Meng China
Mohsen Zand Malaysia
Stefan Becker Germany
Wangmeng Xiang Hong Kong
Yuhang Ming China
Junfei Zhuang relative to Zikai Song China Zikai Song's profile →
Citations per field
00.5×10×15.5×
Zikai Song · 1×
Citations per year

Countries citing papers authored by Junfei Zhuang

Since Specialization
Citations

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

Fields of papers citing papers by Junfei Zhuang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junfei Zhuang

This figure shows the co-authorship network connecting the top 25 collaborators of Junfei Zhuang. A scholar is included among the top collaborators of Junfei Zhuang 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 Junfei Zhuang. Junfei Zhuang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
#WorkIndexed citations
1 5
2
Multi-branch Siamese Network for High Performance Online Visual Tracking
1
3 7
4 93
5 72

About Junfei Zhuang

Junfei Zhuang is a scholar working on Safety, Risk, Reliability and Quality, Computer Vision and Pattern Recognition and Analytical Chemistry, having authored 5 papers that have together received 178 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (4 papers), Image Enhancement Techniques (3 papers) and Fire Detection and Safety Systems (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (110 citations), Safety, Risk, Reliability and Quality (33 citations) and Medical Laboratory Technology (3 citations). Junfei Zhuang has collaborated with scholars based in China and Japan. Frequent co-authors include Hongliang Bai, Yuan Dong, Zhiqun He, Yingruo Fan, Lixiang Duan, Jinjiang Wang, Weidong Cheng, Jianming Cheng, Peiliang Zuo and Gang Wang. Their work appears in journals such as IEEE Access, Neurocomputing and Asian Conference on Machine Learning.

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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