Dianhai Yu
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Computer Networks and Communications
- Signal Processing
- Co-authors
- Daxiang DongHua WuWei HeHaifeng WangYanjun MaXiangyang ZhouYing ChenLi Lü
- Topics
- Topic Modeling (10 papers)Natural Language Processing Techniques (9 papers)Speech Recognition and Synthesis (6 papers)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Dianhai Yu
27 papers receiving 995 citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 846
- Computer Vision and Pattern Recognition 301
- Information Systems 129
- Computer Networks and Communications 51
- Signal Processing 32
Countries citing papers authored by Dianhai Yu
This map shows the geographic impact of Dianhai Yu'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 Dianhai Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dianhai Yu more than expected).
Fields of papers citing papers by Dianhai Yu
This network shows the impact of papers produced by Dianhai Yu. 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 Dianhai Yu. The network helps show where Dianhai Yu may publish in the future.
Co-authorship network of co-authors of Dianhai Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Dianhai Yu. A scholar is included among the top collaborators of Dianhai Yu 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 Dianhai Yu. Dianhai Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 29 | |
| 4 | 25 | |
| 5 | 4 | |
| 6 | 3 | |
| 7 | 24 | |
| 8 | 12 | |
| 9 | 0 | |
| 10 | 13 | |
| 11 | 5 | |
| 12 | A New Method of Region Embedding for Text Classification | 31 |
| 13 | 184 | |
| 14 | 130 | |
| 15 | Multi-Task Learning for Multiple Language Translationbreakdown → | 316 |
| 16 | Cross-lingual Projections between Languages from Different Families | 3 |
| 17 | Generalization of Words for Chinese Dependency Parsing | 4 |
| 18 | Compound Embedding Features for Semi-supervised Learning | 17 |
| 19 | 4 | |
| 20 | An Improved CRF based Chinese Language Processing System for SIGHAN Bakeoff 2007 | 3 |
About Dianhai Yu
Dianhai Yu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 28 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Natural Language Processing Techniques (9 papers) and Speech Recognition and Synthesis (6 papers). The work is most often cited by research in Artificial Intelligence (846 citations), Computer Vision and Pattern Recognition (301 citations) and Information Systems (129 citations). Dianhai Yu has collaborated with scholars based in China, United States and France. Frequent co-authors include Daxiang Dong, Hua Wu, Wei He, Haifeng Wang, Yanjun Ma, Haifeng Wang, Xiangyang Zhou, Ying Chen, Li Lü and Yi Liu. Their work appears in journals such as IEEE Transactions on Cybernetics, Neurocomputing and Neural Networks.
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.