Loong‐Fah Cheong

3.6k citations
66 papers · 2.1k indexed · h-index 25

Loong‐Fah Cheong

62 papers receiving 2.1k citations

Peers

Loong‐Fah Cheong
Comparison fields: 5 of 104
  • Computer Vision and Pattern Recognition 1.9k
  • Aerospace Engineering 330
  • Artificial Intelligence 315
  • Media Technology 224
  • Biomedical Engineering 142
Replace Pietro Pala with:
Pietro Pala Italy
Honggang Zhang China
Jean‐Charles Bazin South Korea
Saad Ali United States
Joseph J. Lim United States
Wenxiu Sun Hong Kong
Steve Maybank United Kingdom
Esther Koller-Meier Switzerland
Philippos Mordohai United States
Tat‐Jen Cham Singapore
Loong‐Fah Cheong relative to Pietro Pala Italy Pietro Pala's profile →
Citations per field
00.5×3.3×
Pietro Pala · 1×
Citations per year

Countries citing papers authored by Loong‐Fah Cheong

Since Specialization
Citations

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

Fields of papers citing papers by Loong‐Fah Cheong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Loong‐Fah Cheong. 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 Loong‐Fah Cheong. The network helps show where Loong‐Fah Cheong may publish in the future.

Co-authorship network of co-authors of Loong‐Fah Cheong

This figure shows the co-authorship network connecting the top 25 collaborators of Loong‐Fah Cheong. A scholar is included among the top collaborators of Loong‐Fah Cheong 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 Loong‐Fah Cheong. Loong‐Fah Cheong 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 14
2 34
3 37
4 0
5 4
6 95
7 204
8 0
9 41
10 245
11 2
12
Formulation and Use of Time-to-Collision in Content-Based Retrieval
1
13 6
14 19
15 54
16 0
17 11
18 6
19 7
20 13

About Loong‐Fah Cheong

Loong‐Fah Cheong is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 66 papers that have together received 2.1k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (42 papers), Advanced Image and Video Retrieval Techniques (17 papers) and Optical measurement and interference techniques (16 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.9k citations), Computer Graphics and Computer-Aided Design (89 citations) and Media Technology (224 citations). Loong‐Fah Cheong has collaborated with scholars based in Singapore, United States and China. Frequent co-authors include Hee Lin Wang, Shuicheng Yan, Robby T. Tan, Ju Sun, Ruoteng Li, Zhuwen Li, Nianjuan Jiang, Tat‐Seng Chua, Ping Tan and Steven Zhiying Zhou. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and ACM Transactions on Graphics.

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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