Kaican Li
Impact in
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Process Chemistry and Technology top 10%
Papers in
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- Domain Adaptation and Few-Shot Learning 3
- Bayesian Methods and Mixture Models 3
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- Face and Expression Recognition 2
- Co-authors
- Xiaojuan Qi (1 shared paper)Michelle Shu (1 shared paper)Xiaoyong Shen (1 shared paper)Jiaya Jia (1 shared paper)Ruiyu Li (1 shared paper)Xiangfang Peng (3 shared papers)Binyi Chen (2 shared papers)Tairong Kuang (1 shared paper)
In The Last Decade
Kaican Li
15 papers receiving 377 citations
Peers
Comparison fields: 5 of 66
- Computer Vision and Pattern Recognition 220
- Process Chemistry and Technology 30
- Polymers and Plastics 91
- Biomaterials 66
- Artificial Intelligence 112
Countries citing papers authored by Kaican Li
This map shows the geographic impact of Kaican 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 Kaican Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaican Li more than expected).
Fields of papers citing papers by Kaican Li
This network shows the impact of papers produced by Kaican 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 Kaican Li. The network helps show where Kaican Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Kaican Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 154 | |
| 2 | 2022 | 68 | |
| 3 | 2017 | 66 | |
| 4 | 2022 | 36 | |
| 5 | 2015 | 21 | |
| 6 | 2015 | 12 | |
| 7 | 2003 | 6 | |
| 8 | Is a Green Screen Really Necessary for Real-Time Human Matting? | 2020 | 3 |
| 9 | 2023 | 3 | |
| 10 | 2009 | 3 | |
| 11 | 2003 | 3 | |
| 12 | 2018 | 3 | |
| 13 | 2005 | 2 | |
| 14 | 2020 | 1 | |
| 15 | 2001 | 1 | |
| 16 | Maximum Kullback-Leibler Distance of Some Conventional Distributions | 2007 | 0 |
| 17 | 2022 | 0 |
About Kaican Li
Kaican Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Polymers and Plastics, Biomaterials and Statistics and Probability, having authored 17 papers that have together received 382 indexed citations. Recurring topics across this work include biodegradable polymer synthesis and properties (3 papers), Polymer Foaming and Composites (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Bayesian Methods and Mixture Models (3 papers), Face and Expression Recognition (2 papers), Statistical Methods and Bayesian Inference (2 papers), Advanced Statistical Methods and Models (2 papers) and Statistical Methods and Inference (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (220 citations), Process Chemistry and Technology (30 citations), Polymers and Plastics (91 citations), Biomaterials (66 citations) and Artificial Intelligence (112 citations). Kaican Li has collaborated with scholars based in China, Hong Kong and Sweden. Frequent co-authors include Xiaojuan Qi, Michelle Shu, Xiaoyong Shen, Jiaya Jia, Ruiyu Li, Xiangfang Peng, Binyi Chen, Tairong Kuang, Rynson W. H. Lau and Qiong Yan. Their work appears in journals such as Polymer Composites, Computational Statistics & Data Analysis, RSC Advances, Composites Part B Engineering and Statistics & Probability Letters.
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.