Xin He
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Electrical and Electronic Engineering
- Media Technology top 2%
- Topics
- Advanced Data and IoT Technologies (5 papers)Advanced Neural Network Applications (5 papers)Telecommunications and Broadcasting Technologies (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsEuropean Journal of Operational Research
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Xin He
55 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Artificial Intelligence 682
- Computer Vision and Pattern Recognition 610
- Radiology, Nuclear Medicine and Imaging 411
- Electrical and Electronic Engineering 283
- Media Technology 231
Countries citing papers authored by Xin He
This map shows the geographic impact of Xin He'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 Xin He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin He more than expected).
Fields of papers citing papers by Xin He
This network shows the impact of papers produced by Xin He. 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 Xin He. The network helps show where Xin He may publish in the future.
Co-authorship network of co-authors of Xin He
This figure shows the co-authorship network connecting the top 25 collaborators of Xin He. A scholar is included among the top collaborators of Xin He 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 Xin He. Xin He 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 | 0 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 9 | |
| 8 | 42 | |
| 9 | 14 | |
| 10 | 3 | |
| 11 | 15 | |
| 12 | Benchmarking the Performance and Power of AI Accelerators for AI Training | 7 |
| 13 | Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models | 1 |
| 14 | 9 | |
| 15 | 34 | |
| 16 | 204 | |
| 17 | 1 | |
| 18 | 5 | |
| 19 | 7 | |
| 20 | Hierarchical Support Vector Machines for Audio Classification * | 1 |
About Xin He
Xin He is a scholar working on Management Information Systems, Media Technology and Computer Vision and Pattern Recognition, having authored 62 papers that have together received 2.6k indexed citations. Recurring topics across this work include Advanced Data and IoT Technologies (5 papers), Advanced Neural Network Applications (5 papers) and Telecommunications and Broadcasting Technologies (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (610 citations), Media Technology (231 citations) and Artificial Intelligence (682 citations). Xin He has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xiaowen Chu, Kaiyong Zhao, Cong Yao, Shangbang Long, Meng Liu, Hanliang Shao, Dong Yuanhua, Ling Li, Jiafeng Jiang and Jiangang Li. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and European Journal of Operational Research.
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.