Hai Liu
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Electrical and Electronic Engineering
- Information Systems top 10%
- Co-authors
- Zhaoli ZhangTingting LiuYoufu LiCheng ZhangNaixue XiongZhifei LiYongjian DengArun Kumar Sangaiah
- Topics
- Human Pose and Action Recognition (6 papers)Face recognition and analysis (5 papers)Hand Gesture Recognition Systems (5 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Hai Liu
26 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Computer Vision and Pattern Recognition 578
- Artificial Intelligence 379
- Biomedical Engineering 124
- Electrical and Electronic Engineering 119
- Information Systems 94
Countries citing papers authored by Hai Liu
This map shows the geographic impact of Hai Liu'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 Hai Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hai Liu more than expected).
Fields of papers citing papers by Hai Liu
This network shows the impact of papers produced by Hai Liu. 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 Hai Liu. The network helps show where Hai Liu may publish in the future.
Co-authorship network of co-authors of Hai Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Hai Liu. A scholar is included among the top collaborators of Hai Liu 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 Hai Liu. Hai Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 5 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 32 | |
| 10 | TransIFC: Invariant Cues-Aware Feature Concentration Learning for Efficient Fine-Grained Bird Image Classificationbreakdown → | 116 |
| 11 | 65 | |
| 12 | ARHPE: Asymmetric Relation-Aware Representation Learning for Head Pose Estimation in Industrial Human–Computer Interactionbreakdown → | 199 |
| 13 | 134 | |
| 14 | Learning Knowledge Graph Embedding With Heterogeneous Relation Attention Networksbreakdown → | 227 |
| 15 | 3 | |
| 16 | 14 | |
| 17 | 27 | |
| 18 | 28 | |
| 19 | The Integration research of configuration software and management information system | 0 |
| 20 | OLAP-based collaborative educational decision | 0 |
About Hai Liu
Hai Liu is a scholar working on Human-Computer Interaction, Developmental Biology and Computer Vision and Pattern Recognition, having authored 30 papers that have together received 1.2k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (6 papers), Face recognition and analysis (5 papers) and Hand Gesture Recognition Systems (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (578 citations), Human-Computer Interaction (92 citations) and Artificial Intelligence (379 citations). Hai Liu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Zhaoli Zhang, Tingting Liu, Youfu Li, Cheng Zhang, Naixue Xiong, Zhifei Li, Yongjian Deng, Arun Kumar Sangaiah, Bing Yang and Motoyuki Sato. Their work appears in journals such as IEEE Transactions on Image Processing, Sensors and IEEE Transactions on Industrial Informatics.
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.