Xiaocheng Feng
- Artificial Intelligence top 0.5%
- Information Systems top 0.5%
- Software top 1%
- Signal Processing top 2%
- Computer Networks and Communications top 5%
- Topics
- Topic Modeling (40 papers)Natural Language Processing Techniques (38 papers)Multimodal Machine Learning Applications (11 papers)
- Journals
- IEEE Transactions on Geoscience and Remote SensingIEEE Transactions on Knowledge and Data EngineeringIEEE Transactions on Neural Systems and Rehabilitation Engineering
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Xiaocheng Feng
55 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 1.9k
- Information Systems 1.2k
- Software 519
- Signal Processing 360
- Computer Networks and Communications 290
Countries citing papers authored by Xiaocheng Feng
This map shows the geographic impact of Xiaocheng Feng'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 Xiaocheng Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaocheng Feng more than expected).
Fields of papers citing papers by Xiaocheng Feng
This network shows the impact of papers produced by Xiaocheng Feng. 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 Xiaocheng Feng. The network helps show where Xiaocheng Feng may publish in the future.
Co-authorship network of co-authors of Xiaocheng Feng
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaocheng Feng. A scholar is included among the top collaborators of Xiaocheng Feng 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 Xiaocheng Feng. Xiaocheng Feng 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 | 1 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 4 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 8 | |
| 15 | 16 | |
| 16 | 40 | |
| 17 | 40 | |
| 18 | Bitext Name Tagging for Cross-lingual Entity Annotation Projection | 7 |
| 19 | English-Chinese Knowledge Base Translation with Neural Network | 7 |
| 20 | Effective LSTMs for Target-Dependent Sentiment Classification | 249 |
About Xiaocheng Feng
Xiaocheng Feng is a scholar working on Artificial Intelligence, Health Informatics and Computer Vision and Pattern Recognition, having authored 65 papers that have together received 2.9k indexed citations. Recurring topics across this work include Topic Modeling (40 papers), Natural Language Processing Techniques (38 papers) and Multimodal Machine Learning Applications (11 papers). The work is most often cited by research in Software (519 citations), Health Informatics (81 citations) and Artificial Intelligence (1.9k citations). Xiaocheng Feng has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Bing Qin, Ting Liu, Duyu Tang, Zhangyin Feng, Nan Duan, Ming Zhou, Daxin Jiang, Linjun Shou, Daya Guo and Ming Gong. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Neural Systems and Rehabilitation 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.