Tong Xiao
- Computer Vision and Pattern Recognition top 0.1%
- Artificial Intelligence top 0.5%
- Biomedical Engineering top 2%
- Ocean Engineering top 2%
- Electrical and Electronic Engineering
- Co-authors
- Xiaogang WangWei LiRui ZhaoHongsheng LiWanli OuyangLiang LinShuang LiBochao Wang
- Topics
- Natural Language Processing Techniques (67 papers)Topic Modeling (65 papers)Speech Recognition and Synthesis (19 papers)
- Journals
- PLoS ONEIEEE Transactions on Pattern Analysis and Machine IntelligenceNature Nanotechnology
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Tong Xiao
124 papers receiving 5.9k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Computer Vision and Pattern Recognition 4.4k
- Artificial Intelligence 1.5k
- Biomedical Engineering 1.4k
- Ocean Engineering 257
- Electrical and Electronic Engineering 219
Countries citing papers authored by Tong Xiao
This map shows the geographic impact of Tong Xiao'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 Tong Xiao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tong Xiao more than expected).
Fields of papers citing papers by Tong Xiao
This network shows the impact of papers produced by Tong Xiao. 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 Tong Xiao. The network helps show where Tong Xiao may publish in the future.
Co-authorship network of co-authors of Tong Xiao
This figure shows the co-authorship network connecting the top 25 collaborators of Tong Xiao. A scholar is included among the top collaborators of Tong Xiao 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 Tong Xiao. Tong Xiao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 0 | |
| 3 | 10 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 55 | |
| 8 | 11 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 3 | |
| 12 | 0 | |
| 13 | 45 | |
| 14 | Joint Detection and Identification Feature Learning for Person Searchbreakdown → | 582 |
| 15 | 180 | |
| 16 | Implicit Syntactic Features for Target-dependent Sentiment Analysis | 4 |
| 17 | DeepReID: Deep Filter Pairing Neural Network for Person Re-identificationbreakdown → | 1754 |
| 18 | Effective Incorporation of Source Syntax into Hierarchical Phrase-based Translation | 2 |
| 19 | The University of Cambridge Russian-English System at WMT13 | 6 |
| 20 | 1 |
About Tong Xiao
Tong Xiao is a scholar working on Artificial Intelligence, Computational Mathematics and Computer Vision and Pattern Recognition, having authored 153 papers that have together received 6.0k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (67 papers), Topic Modeling (65 papers) and Speech Recognition and Synthesis (19 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (4.4k citations), Artificial Intelligence (1.5k citations) and Biomedical Engineering (1.4k citations). Tong Xiao has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xiaogang Wang, Wei Li, Rui Zhao, Hongsheng Li, Wanli Ouyang, Liang Lin, Shuang Li, Bochao Wang, Tian Xia and Yi Yang. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Nature Nanotechnology.
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.