Kaiqi Huang
- Computer Vision and Pattern Recognition top 0.1%
- Artificial Intelligence top 0.5%
- Biomedical Engineering top 5%
- Aerospace Engineering top 2%
- Media Technology top 0.5%
- Topics
- Video Surveillance and Tracking Methods (85 papers)Advanced Image and Video Retrieval Techniques (51 papers)Advanced Neural Network Applications (41 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologySafety, Risk, Reliability and Quality
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingComputers in Human Behavior
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Kaiqi Huang
185 papers receiving 6.5k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Computer Vision and Pattern Recognition 5.9k
- Artificial Intelligence 1.5k
- Biomedical Engineering 916
- Aerospace Engineering 633
- Media Technology 539
Countries citing papers authored by Kaiqi Huang
This map shows the geographic impact of Kaiqi 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 Kaiqi Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaiqi Huang more than expected).
Fields of papers citing papers by Kaiqi Huang
This network shows the impact of papers produced by Kaiqi 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 Kaiqi Huang. The network helps show where Kaiqi Huang may publish in the future.
Co-authorship network of co-authors of Kaiqi Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Kaiqi Huang. A scholar is included among the top collaborators of Kaiqi 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 Kaiqi Huang. Kaiqi 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 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 5 | |
| 6 | 14 | |
| 7 | 8 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 25 | |
| 13 | 33 | |
| 14 | 138 | |
| 15 | DF 2 Net: Discriminative Feature Learning and Fusion Network for RGB-D Indoor Scene Classification | 23 |
| 16 | A2-RL: Aesthetics Aware Reinforcement Learning for Automatic Image Cropping. | 5 |
| 17 | 16 | |
| 18 | 1 | |
| 19 | Fuzzy reliability allocation method for engine based on the experts' knowledge | 6 |
| 20 | 19 |
About Kaiqi Huang
Kaiqi Huang is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Artificial Intelligence, having authored 198 papers that have together received 6.7k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (85 papers), Advanced Image and Video Retrieval Techniques (51 papers) and Advanced Neural Network Applications (41 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.9k citations), Media Technology (539 citations) and Safety, Risk, Reliability and Quality (517 citations). Kaiqi Huang has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Xin Zhao, Tieniu Tan, Lianghua Huang, Xiaotang Chen, Zhang Zhang, Dangwei Li, Tieniu Tan, Ran He, Zhaoxiang Zhang and Junge Zhang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Computers in Human Behavior.
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.