Kai Kang
- Computer Vision and Pattern Recognition
- Media Technology
- Artificial Intelligence
- Electrical and Electronic Engineering
- Management Science and Operations Research
- Co-authors
- Xingang LiuHanspeter PfisterDaniel HaehnQiaoyu WangYinbo LiuVincent CasserYang CaoZengfu Wang
- Topics
- Advanced Image Fusion Techniques (2 papers)Visual Attention and Saliency Detection (2 papers)Image and Video Quality Assessment (2 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Kai Kang
15 papers receiving 69 citations
Peers
Comparison fields: 5 of 42
- Computer Vision and Pattern Recognition 38
- Media Technology 18
- Artificial Intelligence 10
- Electrical and Electronic Engineering 8
- Management Science and Operations Research 7
Countries citing papers authored by Kai Kang
This map shows the geographic impact of Kai Kang'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 Kai Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Kang more than expected).
Fields of papers citing papers by Kai Kang
This network shows the impact of papers produced by Kai Kang. 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 Kai Kang. The network helps show where Kai Kang may publish in the future.
Co-authorship network of co-authors of Kai Kang
This figure shows the co-authorship network connecting the top 25 collaborators of Kai Kang. A scholar is included among the top collaborators of Kai Kang 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 Kai Kang. Kai Kang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 6 | |
| 3 | 12 | |
| 4 | Fast Mitochondria Detection for Connectomics | 12 |
| 5 | 4 | |
| 6 | 0 | |
| 7 | Research on Pricing Decision of Double Competition Closed-loop Supply Chain with Uncertainty of Recovery Quantity | 1 |
| 8 | 7 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 10 | |
| 12 | 5 | |
| 13 | 1 | |
| 14 | 6 | |
| 15 | 2 | |
| 16 | Ant colony and particle swarm optimization algorithm-based solution to multi-mode resource-constrained project scheduling problem | 2 |
About Kai Kang
Kai Kang is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Energy Engineering and Power Technology, having authored 16 papers that have together received 74 indexed citations. Recurring topics across this work include Advanced Image Fusion Techniques (2 papers), Visual Attention and Saliency Detection (2 papers) and Image and Video Quality Assessment (2 papers). The work is most often cited by research in Structural Biology (4 citations), Media Technology (18 citations) and Computer Vision and Pattern Recognition (38 citations). Kai Kang has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Xingang Liu, Hanspeter Pfister, Daniel Haehn, Qiaoyu Wang, Yinbo Liu, Vincent Casser, Yang Cao, Zengfu Wang, Jing Zhang and Xun Zhao. Their work appears in journals such as IEEE Access, Multimedia Tools and Applications and IEEE Systems Journal.
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.