Xinyu Liu
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 10%
- Oncology
- Information Systems top 10%
- Co-authors
- Yixuan YuanWuyang LiXiaoguang DiVictor Hugo C. de AlbuquerqueShuai WangShuai LiuKhan MuhammadAmir H. Gandomi
- Topics
- Advanced Neural Network Applications (16 papers)Colorectal Cancer Screening and Detection (11 papers)Domain Adaptation and Few-Shot Learning (10 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Xinyu Liu
92 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Computer Vision and Pattern Recognition 556
- Artificial Intelligence 547
- Radiology, Nuclear Medicine and Imaging 121
- Oncology 113
- Information Systems 102
Countries citing papers authored by Xinyu Liu
This map shows the geographic impact of Xinyu 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 Xinyu Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinyu Liu more than expected).
Fields of papers citing papers by Xinyu Liu
This network shows the impact of papers produced by Xinyu 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 Xinyu Liu. The network helps show where Xinyu Liu may publish in the future.
Co-authorship network of co-authors of Xinyu Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Xinyu Liu. A scholar is included among the top collaborators of Xinyu 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 Xinyu Liu. Xinyu 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 | 3 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 6 | |
| 9 | 1 | |
| 10 | 0 | |
| 11 | 5 | |
| 12 | 1 | |
| 13 | 7 | |
| 14 | 9 | |
| 15 | 8 | |
| 16 | 12 | |
| 17 | 36 | |
| 18 | 8 | |
| 19 | 3 | |
| 20 | 15 |
About Xinyu Liu
Xinyu Liu is a scholar working on Computer Vision and Pattern Recognition, Computational Mathematics and Artificial Intelligence, having authored 112 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (16 papers), Colorectal Cancer Screening and Detection (11 papers) and Domain Adaptation and Few-Shot Learning (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (556 citations), Artificial Intelligence (547 citations) and Computational Mathematics (9 citations). Xinyu Liu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Yixuan Yuan, Wuyang Li, Xiaoguang Di, Victor Hugo C. de Albuquerque, Shuai Wang, Shuai Liu, Khan Muhammad, Amir H. Gandomi, Mahmoud Daneshmand and Long Qian. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.