Yue Hu
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Statistical and Nonlinear Physics top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Chuan ZhouJia WuJing YuLi GaoQi WuHong YangZengchang QinWeifeng Zhang
- Topics
- Topic Modeling (31 papers)Natural Language Processing Techniques (21 papers)Multimodal Machine Learning Applications (18 papers)
- Journals
- Angewandte Chemie International EditionIEEE Transactions on Image ProcessingIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Yue Hu
63 papers receiving 787 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 599
- Computer Vision and Pattern Recognition 285
- Information Systems 225
- Statistical and Nonlinear Physics 62
- Computer Networks and Communications 60
Countries citing papers authored by Yue Hu
This map shows the geographic impact of Yue Hu'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 Yue Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yue Hu more than expected).
Fields of papers citing papers by Yue Hu
This network shows the impact of papers produced by Yue Hu. 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 Yue Hu. The network helps show where Yue Hu may publish in the future.
Co-authorship network of co-authors of Yue Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Yue Hu. A scholar is included among the top collaborators of Yue Hu 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 Yue Hu. Yue Hu 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 | 2 | |
| 3 | 0 | |
| 4 | 22 | |
| 5 | 11 | |
| 6 | 1 | |
| 7 | 15 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 33 | |
| 11 | 1 | |
| 12 | On Learning Universal Representations Across Languages | 33 |
| 13 | 12 | |
| 14 | 0 | |
| 15 | 1 | |
| 16 | 26 | |
| 17 | 16 | |
| 18 | 76 | |
| 19 | Multi-modal Learning with Prior Visual Relation Reasoning. | 8 |
| 20 | Status of China Cotton Trade and Analysis on Its International Competition | 1 |
About Yue Hu
Yue Hu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Transportation, having authored 69 papers that have together received 811 indexed citations. Recurring topics across this work include Topic Modeling (31 papers), Natural Language Processing Techniques (21 papers) and Multimodal Machine Learning Applications (18 papers). The work is most often cited by research in Artificial Intelligence (599 citations), Computer Vision and Pattern Recognition (285 citations) and Information Systems (225 citations). Yue Hu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Chuan Zhou, Jia Wu, Jing Yu, Li Gao, Qi Wu, Hong Yang, Zengchang Qin, Weifeng Zhang, Li Guo and Jianlong Tan. Their work appears in journals such as Angewandte Chemie International Edition, IEEE Transactions on Image Processing and IEEE Transactions on Knowledge and Data Engineering.
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.