Kim–Hui Yap

2.6k citations
138 papers · 1.6k indexed · h-index 22
Topics
Advanced Image and Video Retrieval Techniques (42 papers)Image and Signal Denoising Methods (27 papers)Advanced Image Processing Techniques (27 papers)
Partner nations
SingaporeChinaHong Kong

In The Last Decade

Kim–Hui Yap

121 papers receiving 1.5k citations

Peers

Kim–Hui Yap
Comparison fields: 5 of 100
  • Computer Vision and Pattern Recognition 1.3k
  • Media Technology 329
  • Artificial Intelligence 186
  • Biomedical Engineering 174
  • Computational Mechanics 140
Replace Bo Peng with:
Bo Peng China
Renjie Liao Canada
Yigang Cen China
Steve Maybank United Kingdom
Thomas H. Li China
Jiangning Zhang China
Simone Milani Italy
Marc Proesmans Belgium
Anhong Wang China
Shuyuan Zhu China
Kim–Hui Yap relative to Bo Peng China Bo Peng's profile →
Citations per field
00.5×10×15.5×
Bo Peng · 1×
Citations per year

Countries citing papers authored by Kim–Hui Yap

Since Specialization
Citations

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

Fields of papers citing papers by Kim–Hui Yap

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kim–Hui Yap. 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 Kim–Hui Yap. The network helps show where Kim–Hui Yap may publish in the future.

Co-authorship network of co-authors of Kim–Hui Yap

This figure shows the co-authorship network connecting the top 25 collaborators of Kim–Hui Yap. A scholar is included among the top collaborators of Kim–Hui Yap 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 Kim–Hui Yap. Kim–Hui Yap 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 2
2 0
3 0
4 4
5 2
6 2
7 0
8 0
9 7
10 16
11 1
12 7
13
Autoregressive Generative Adversarial Networks
1
14
The Unusual Effectiveness of Averaging in GAN Training
10
15 1
16 25
17 3
18 2
19 89
20 34

About Kim–Hui Yap

Kim–Hui Yap is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 138 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (42 papers), Image and Signal Denoising Methods (27 papers) and Advanced Image Processing Techniques (27 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.3k citations), Media Technology (329 citations) and Geology (83 citations). Kim–Hui Yap has collaborated with scholars based in Singapore, China and Hong Kong. Frequent co-authors include Lap‐Pui Chau, Sharmili Roy, Kui Wu, Yu He, Tao Chen, Zhen Li, Li Chen, Ling Guan, Jiacheng Wei and Guosheng Lin. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Signal Processing and Optics Letters.

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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