Lele Cheng
- Electronic, Optical and Magnetic Materials top 10%
- Aerospace Engineering top 10%
- Polymers and Plastics
- Biomedical Engineering
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Bianying WenMunan QiuYang ZhangYing YuQiqi HouYihong GongJinjun WangXiangteng He
- Topics
- Advanced Memory and Neural Computing (3 papers)Face recognition and analysis (3 papers)Generative Adversarial Networks and Image Synthesis (2 papers)
- Cited by
- Nuclear Energy and EngineeringElectronic, Optical and Magnetic MaterialsPolymers and Plastics
- Journals
- SHILAP Revista de lepidopterologíaApplied Physics LettersIEEE Transactions on Pattern Analysis and Machine Intelligence
In The Last Decade
Lele Cheng
16 papers receiving 375 citations
Peers
Comparison fields: 5 of 53
- Electronic, Optical and Magnetic Materials 224
- Aerospace Engineering 137
- Polymers and Plastics 86
- Biomedical Engineering 81
- Computer Vision and Pattern Recognition 73
Countries citing papers authored by Lele Cheng
This map shows the geographic impact of Lele Cheng'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 Lele Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lele Cheng more than expected).
Fields of papers citing papers by Lele Cheng
This network shows the impact of papers produced by Lele Cheng. 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 Lele Cheng. The network helps show where Lele Cheng may publish in the future.
Co-authorship network of co-authors of Lele Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Lele Cheng. A scholar is included among the top collaborators of Lele Cheng 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 Lele Cheng. Lele Cheng 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 | 5 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 5 | |
| 7 | 11 | |
| 8 | 8 | |
| 9 | 0 | |
| 10 | 17 | |
| 11 | 2 | |
| 12 | 11 | |
| 13 | 18 | |
| 14 | 4 | |
| 15 | 254 | |
| 16 | 30 | |
| 17 | 14 |
About Lele Cheng
Lele Cheng is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Signal Processing, having authored 17 papers that have together received 387 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (3 papers), Face recognition and analysis (3 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Nuclear Energy and Engineering (12 citations), Electronic, Optical and Magnetic Materials (224 citations) and Polymers and Plastics (86 citations). Lele Cheng has collaborated with scholars based in China, Singapore and Poland. Frequent co-authors include Bianying Wen, Munan Qiu, Yang Zhang, Ying Yu, Qiqi Hou, Yihong Gong, Jinjun Wang, Xiangteng He, Yuxin Peng and Xiangshui Miao. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Physics Letters 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.