Kaicong Huang
- Computer Vision and Pattern Recognition top 5%
- Human-Computer Interaction top 5%
- Aerospace Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering
- Co-authors
- Mohan M. TrivediIvana Medvedec MikićT. GandhiLiang WangPeng DaiShengchun WangChenxi LiuTarak Gandhi
- Topics
- Video Surveillance and Tracking Methods (6 papers)Indoor and Outdoor Localization Technologies (2 papers)Advanced Vision and Imaging (2 papers)
- Journals
- IEEE Transactions on Instrumentation and MeasurementIEEE Transactions on Systems Man and Cybernetics - Part A Systems and HumansIEEE Intelligent Systems
- Partner nations
- United StatesChina
In The Last Decade
Kaicong Huang
10 papers receiving 278 citations
Peers
Comparison fields: 5 of 48
- Computer Vision and Pattern Recognition 225
- Human-Computer Interaction 64
- Aerospace Engineering 40
- Artificial Intelligence 38
- Electrical and Electronic Engineering 38
Countries citing papers authored by Kaicong Huang
This map shows the geographic impact of Kaicong Huang'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 Kaicong Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaicong Huang more than expected).
Fields of papers citing papers by Kaicong Huang
This network shows the impact of papers produced by Kaicong Huang. 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 Kaicong Huang. The network helps show where Kaicong Huang may publish in the future.
Co-authorship network of co-authors of Kaicong Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Kaicong Huang. A scholar is included among the top collaborators of Kaicong Huang 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 Kaicong Huang. Kaicong Huang 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 | 1 | |
| 3 | 5 | |
| 4 | 44 | |
| 5 | 56 | |
| 6 | 2 | |
| 7 | 53 | |
| 8 | 64 | |
| 9 | 9 | |
| 10 | 20 | |
| 11 | 49 |
About Kaicong Huang
Kaicong Huang is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality and Signal Processing, having authored 11 papers that have together received 303 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (6 papers), Indoor and Outdoor Localization Technologies (2 papers) and Advanced Vision and Imaging (2 papers). The work is most often cited by research in Human-Computer Interaction (64 citations), Computer Vision and Pattern Recognition (225 citations) and Signal Processing (37 citations). Kaicong Huang has collaborated with scholars based in United States and China. Frequent co-authors include Mohan M. Trivedi, Ivana Medvedec Mikić, T. Gandhi, Liang Wang, Peng Dai, Shengchun Wang, Chenxi Liu, Tarak Gandhi and Ruimin Ke. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans and IEEE Intelligent Systems.
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.