Simon Tong
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Signal Processing top 5%
- Information Systems top 10%
- Media Technology top 5%
- Topics
- Machine Learning and Algorithms (6 papers)Machine Learning and Data Classification (3 papers)Advanced Image and Video Retrieval Techniques (2 papers)
- Journals
- Genetics ResearchNeural Information Processing SystemsInternational Joint Conference on Artificial Intelligence
- Partner nations
- United StatesFranceUnited Kingdom
In The Last Decade
Simon Tong
8 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 904
- Computer Vision and Pattern Recognition 823
- Signal Processing 120
- Information Systems 101
- Media Technology 101
Countries citing papers authored by Simon Tong
This map shows the geographic impact of Simon Tong'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 Simon Tong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Tong more than expected).
Fields of papers citing papers by Simon Tong
This network shows the impact of papers produced by Simon Tong. 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 Simon Tong. The network helps show where Simon Tong may publish in the future.
Co-authorship network of co-authors of Simon Tong
This figure shows the co-authorship network connecting the top 25 collaborators of Simon Tong. A scholar is included among the top collaborators of Simon Tong 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 Simon Tong. Simon Tong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Support Vector Machine Concept-Dependent Active Learning for Image Retrieval | 36 |
| 2 | Active learning for structure in Bayesian networks | 86 |
| 3 | Support vector machine active learning for image retrievalbreakdown → | 900 |
| 4 | Active learning: theory and applications | 125 |
| 5 | Active Learning for Parameter Estimation in Bayesian Networks | 90 |
| 6 | Restricted Bayes Optimal Classifiers | 28 |
| 7 | Support Vector Machine Active Learning with Application sto Text Classification | 281 |
| 8 | 14 |
About Simon Tong
Simon Tong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 8 papers that have together received 1.6k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (6 papers), Machine Learning and Data Classification (3 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (823 citations), Artificial Intelligence (904 citations) and Media Technology (101 citations). Simon Tong has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Edward Yi Chang, Daphne Koller, M. S. Ridout and K. R. Tobutt. Their work appears in journals such as Genetics Research, Neural Information Processing Systems and International Joint Conference on Artificial 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.