Liangyu Huo
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 10%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Signal Processing top 10%
- Topics
- Visual Attention and Saliency Detection (5 papers)Opportunistic and Delay-Tolerant Networks (5 papers)Satellite Communication Systems (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Networks and CommunicationsAerospace Engineering
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on CommunicationsIEEE Transactions on Vehicular Technology
- Partner nations
- ChinaUnited KingdomLuxembourg
In The Last Decade
Liangyu Huo
13 papers receiving 422 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 187
- Aerospace Engineering 153
- Computer Networks and Communications 150
- Electrical and Electronic Engineering 104
- Signal Processing 66
Countries citing papers authored by Liangyu Huo
This map shows the geographic impact of Liangyu Huo'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 Liangyu Huo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liangyu Huo more than expected).
Fields of papers citing papers by Liangyu Huo
This network shows the impact of papers produced by Liangyu Huo. 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 Liangyu Huo. The network helps show where Liangyu Huo may publish in the future.
Co-authorship network of co-authors of Liangyu Huo
This figure shows the co-authorship network connecting the top 25 collaborators of Liangyu Huo. A scholar is included among the top collaborators of Liangyu Huo 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 Liangyu Huo. Liangyu Huo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 5 | |
| 3 | 22 | |
| 4 | 9 | |
| 5 | 60 | |
| 6 | 71 | |
| 7 | 2 | |
| 8 | 11 | |
| 9 | 37 | |
| 10 | 7 | |
| 11 | 3 | |
| 12 | 179 | |
| 13 | Modeling Attention in Panoramic Video: A Deep Reinforcement Learning Approach. | 3 |
About Liangyu Huo
Liangyu Huo is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Signal Processing, having authored 13 papers that have together received 425 indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (5 papers), Opportunistic and Delay-Tolerant Networks (5 papers) and Satellite Communication Systems (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (187 citations), Computer Networks and Communications (150 citations) and Aerospace Engineering (153 citations). Liangyu Huo has collaborated with scholars based in China, United Kingdom and Luxembourg. Frequent co-authors include Chen Han, Haichao Wang, Mai Xu, Zulin Wang, Yuhang Song, Jianyi Wang, Minglang Qiao, Aijun Liu, Xiaohu Liang and Xian Liu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Communications and IEEE Transactions on Vehicular Technology.
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.