S. H. Ong
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 2%
- Statistics and Probability top 1%
- Media Technology top 1%
- Signal Processing top 5%
- Co-authors
- Ramakrishnan MukundanRaveendran ParamesranPew‐Thian YapRamesh C. GuptaYap Bee WahSubir DasH. M. SrivastavaHossein Jafari
- Topics
- Statistical Distribution Estimation and Applications (56 papers)Bayesian Methods and Mixture Models (46 papers)Statistical Methods and Bayesian Inference (27 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
In The Last Decade
S. H. Ong
128 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Computer Vision and Pattern Recognition 1.3k
- Artificial Intelligence 505
- Statistics and Probability 463
- Media Technology 262
- Signal Processing 190
Countries citing papers authored by S. H. Ong
This map shows the geographic impact of S. H. Ong'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 S. H. Ong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. H. Ong more than expected).
Fields of papers citing papers by S. H. Ong
This network shows the impact of papers produced by S. H. Ong. 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 S. H. Ong. The network helps show where S. H. Ong may publish in the future.
Co-authorship network of co-authors of S. H. Ong
This figure shows the co-authorship network connecting the top 25 collaborators of S. H. Ong. A scholar is included among the top collaborators of S. H. Ong 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 S. H. Ong. S. H. Ong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 6 | |
| 10 | 11 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 38 | |
| 14 | 15 | |
| 15 | 34 | |
| 16 | 2 | |
| 17 | 13 | |
| 18 | 3 | |
| 19 | 18 | |
| 20 | 1 |
About S. H. Ong
S. H. Ong is a scholar working on Statistics and Probability, Modeling and Simulation and Numerical Analysis, having authored 140 papers that have together received 2.6k indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (56 papers), Bayesian Methods and Mixture Models (46 papers) and Statistical Methods and Bayesian Inference (27 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.3k citations), Statistics and Probability (463 citations) and Modeling and Simulation (153 citations). S. H. Ong has collaborated with scholars based in Malaysia, India and Canada. Frequent co-authors include Ramakrishnan Mukundan, Raveendran Paramesran, Pew‐Thian Yap, Ramesh C. Gupta, Yap Bee Wah, Subir Das, H. M. Srivastava, Hossein Jafari, Anup Singh and Subrata Chakraborty. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.