Lifang Chen

951 citations
49 papers · 614 indexed · h-index 13
Topics
Advanced Neural Network Applications (6 papers)Imbalanced Data Classification Techniques (5 papers)Vehicle License Plate Recognition (4 papers)
Partner nations
ChinaUnited StatesTaiwan

In The Last Decade

Lifang Chen

41 papers receiving 592 citations

Peers

Lifang Chen
Comparison fields: 5 of 106
  • Computer Vision and Pattern Recognition 233
  • Artificial Intelligence 115
  • Information Systems 75
  • Electrical and Electronic Engineering 70
  • Media Technology 69
Replace Jiachen Liu with:
Jiachen Liu China
Vivek Agarwal United States
Mahmut Kaya Türkiye
Tong Jia China
Khalid Almohammadi Saudi Arabia
Song Sun China
T Anjali India
Lars Nolle United Kingdom
Lifang Chen relative to Jiachen Liu China Jiachen Liu's profile →
Citations per field
00.5×3.3×
Jiachen Liu · 1×
Citations per year

Countries citing papers authored by Lifang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Lifang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lifang Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Lifang Chen. A scholar is included among the top collaborators of Lifang Chen 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 Lifang Chen. Lifang Chen 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 0
2 15
3 1
4 0
5 1
6 5
7 32
8 23
9 5
10 3
11 8
12 7
13
A multi-granularity ensemble classification algorithm for imbalanced data
0
14 135
15 3
16 1
17 5
18 20
19
A Survey and Discussion on Oral English Proficiency of Non-English Majors
1
20 2

About Lifang Chen

Lifang Chen is a scholar working on Space and Planetary Science, Computer Vision and Pattern Recognition and Media Technology, having authored 49 papers that have together received 614 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (6 papers), Imbalanced Data Classification Techniques (5 papers) and Vehicle License Plate Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (233 citations), Media Technology (69 citations) and Software (29 citations). Lifang Chen has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Zhichao Chen, Jie Yang, Zhicheng Feng, Tao Gao, Chunxia Zhao, Li Wan, Limin Jia, Mengyuan Yang, Yu Tang and Mei-Lan Tang. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Resources Conservation and Recycling.

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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