Chengjun Liu

4.2k citations
34 papers · 2.8k indexed · 1 hit paper · h-index 17
Topics
Face and Expression Recognition (27 papers)Image Retrieval and Classification Techniques (15 papers)Advanced Image and Video Retrieval Techniques (11 papers)

In The Last Decade

Chengjun Liu

32 papers receiving 2.6k citations

Hit Papers

Gabor feature based classification using the enhanced fis...200220262010201820024008001.2k

Peers

Chengjun Liu
Comparison fields: 5 of 124
  • Computer Vision and Pattern Recognition 2.4k
  • Signal Processing 754
  • Media Technology 531
  • Artificial Intelligence 272
  • Atmospheric Science 168
Replace B. Moghaddam with:
B. Moghaddam United States
Yuxiao Hu United States
Hanqing Lu China
Juwei Lu Canada
Bogdan Smołka Poland
Tyng-Luh Liu Taiwan
Jinye Peng China
Roberto Brunelli Italy
Nishan Canagarajah United Kingdom
Bhabatosh Chanda India
Chengjun Liu relative to B. Moghaddam United States B. Moghaddam's profile →
Citations per field
00.5×2.8×
B. Moghaddam · 1×
Citations per year

Countries citing papers authored by Chengjun Liu

Since Specialization
Citations

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

Fields of papers citing papers by Chengjun Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chengjun Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Chengjun Liu. A scholar is included among the top collaborators of Chengjun Liu 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 Chengjun Liu. Chengjun Liu 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 1
3 1
4 25
5 46
6 3
7 24
8 5
9 1
10 73
11 35
12 25
13 44
14 395
15 318
16
Gabor feature based classification using the enhanced fisher linear discriminant model for face recognitionbreakdown →
1366
17 7
18 33
19 16
20
Unified Bayesian framework for face recognition
6

About Chengjun Liu

Chengjun Liu is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 34 papers that have together received 2.8k indexed citations. Recurring topics across this work include Face and Expression Recognition (27 papers), Image Retrieval and Classification Techniques (15 papers) and Advanced Image and Video Retrieval Techniques (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.4k citations), Signal Processing (754 citations) and Media Technology (531 citations). Chengjun Liu has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Harry Wechsler, Jian Yang, Qingfeng Liu, Shuo Chen, Lei Zhang, Zhiming Liu, Jian Yang, Jingyu Yang, Shuo Chen and Abhishek Verma. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

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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