Leilei Huang
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Radiology, Nuclear Medicine and Imaging
- Artificial Intelligence
- Oncology
- Co-authors
- Liantang WangZunfu KeYibo FanXiaoyang ZengZhuo WangRan WangYangshan ChenWeizhong Li
- Topics
- Video Coding and Compression Technologies (13 papers)Advanced Vision and Imaging (12 papers)Cancer Mechanisms and Therapy (5 papers)
- Journals
- Scientific ReportsBiochemical and Biophysical Research CommunicationsJournal of Medicinal Chemistry
- Partner nations
- ChinaMontenegro
In The Last Decade
Leilei Huang
38 papers receiving 520 citations
Peers
Comparison fields: 5 of 97
- Molecular Biology 176
- Computer Vision and Pattern Recognition 98
- Radiology, Nuclear Medicine and Imaging 93
- Artificial Intelligence 81
- Oncology 78
Countries citing papers authored by Leilei Huang
This map shows the geographic impact of Leilei Huang'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 Leilei Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leilei Huang more than expected).
Fields of papers citing papers by Leilei Huang
This network shows the impact of papers produced by Leilei Huang. 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 Leilei Huang. The network helps show where Leilei Huang may publish in the future.
Co-authorship network of co-authors of Leilei Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Leilei Huang. A scholar is included among the top collaborators of Leilei Huang 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 Leilei Huang. Leilei Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 17 | |
| 7 | 12 | |
| 8 | 2 | |
| 9 | 11 | |
| 10 | 88 | |
| 11 | 6 | |
| 12 | 14 | |
| 13 | 10 | |
| 14 | 32 | |
| 15 | 1 | |
| 16 | 17 | |
| 17 | 40 | |
| 18 | 10 | |
| 19 | 29 | |
| 20 | Comparative Study on Chemical Components of the Volatile Oil from the Root of Angelica pubescens in Different Habitats | 2 |
About Leilei Huang
Leilei Huang is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Pathology and Forensic Medicine, having authored 43 papers that have together received 523 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (13 papers), Advanced Vision and Imaging (12 papers) and Cancer Mechanisms and Therapy (5 papers). The work is most often cited by research in Signal Processing (73 citations), Computer Vision and Pattern Recognition (98 citations) and Cancer Research (72 citations). Leilei Huang has collaborated with scholars based in China and Montenegro. Frequent co-authors include Liantang Wang, Zunfu Ke, Yibo Fan, Xiaoyang Zeng, Zhuo Wang, Ran Wang, Yangshan Chen, Weizhong Li, Fen Wang and Sui Peng. Their work appears in journals such as Scientific Reports, Biochemical and Biophysical Research Communications and Journal of Medicinal Chemistry.
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.