Xuanchong Li
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Human-Computer Interaction
- Computer Science Applications
- Co-authors
- Alexander G. HauptmannZhenzhong LanMing LinBhiksha RajKai-Min ChangZhiyong ChengJialie ShenXiaojun Chang
- Topics
- Multimodal Machine Learning Applications (4 papers)Video Analysis and Summarization (4 papers)Advanced Image and Video Retrieval Techniques (3 papers)
- Journals
- NeurocomputingITE Transactions on Media Technology and ApplicationsMonash University Research Portal (Monash University)
- Partner nations
- United StatesAustraliaChina
In The Last Decade
Xuanchong Li
9 papers receiving 249 citations
Peers
Comparison fields: 5 of 41
- Computer Vision and Pattern Recognition 219
- Artificial Intelligence 125
- Biomedical Engineering 48
- Human-Computer Interaction 18
- Computer Science Applications 14
Countries citing papers authored by Xuanchong Li
This map shows the geographic impact of Xuanchong Li'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 Xuanchong Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xuanchong Li more than expected).
Fields of papers citing papers by Xuanchong Li
This network shows the impact of papers produced by Xuanchong Li. 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 Xuanchong Li. The network helps show where Xuanchong Li may publish in the future.
Co-authorship network of co-authors of Xuanchong Li
This figure shows the co-authorship network connecting the top 25 collaborators of Xuanchong Li. A scholar is included among the top collaborators of Xuanchong Li 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 Xuanchong Li. Xuanchong Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | Informedia @ TRECVID 2016. | 2 |
| 3 | 17 | |
| 4 | 3 | |
| 5 | 10 | |
| 6 | 33 | |
| 7 | CMU-SMU@TRECVID 2015: Video Hyperlinking | 4 |
| 8 | 176 | |
| 9 | CMU-informedia @ TRECViD 2014 semantic indexing | 2 |
About Xuanchong Li
Xuanchong Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 9 papers that have together received 251 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (4 papers), Video Analysis and Summarization (4 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (219 citations), Artificial Intelligence (125 citations) and Computational Mathematics (2 citations). Xuanchong Li has collaborated with scholars based in United States, Australia and China. Frequent co-authors include Alexander G. Hauptmann, Zhenzhong Lan, Ming Lin, Bhiksha Raj, Kai-Min Chang, Zhiyong Cheng, Jialie Shen, Alexander G. Hauptmann, Xiaojun Chang and Xingzhong Du. Their work appears in journals such as Neurocomputing, ITE Transactions on Media Technology and Applications and Monash University Research Portal (Monash University).
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.