Jie Lin
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Signal Processing top 10%
- Artificial Intelligence
- Computational Mechanics
- Co-authors
- Xi-Le ZhaoJi MingTing‐Zhu HuangDanny CrookesJinghua ZhaoChengtian OuyangXiaohua ZhaoTai-Xiang Jiang
- Topics
- Image and Signal Denoising Methods (14 papers)Advanced Image Fusion Techniques (9 papers)Face and Expression Recognition (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Geoscience and Remote SensingPattern Recognition
- Partner nations
- ChinaUnited KingdomTaiwan
In The Last Decade
Jie Lin
53 papers receiving 394 citations
Peers
Comparison fields: 5 of 95
- Computer Vision and Pattern Recognition 179
- Media Technology 95
- Signal Processing 63
- Artificial Intelligence 57
- Computational Mechanics 56
Countries citing papers authored by Jie Lin
This map shows the geographic impact of Jie Lin'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 Jie Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jie Lin more than expected).
Fields of papers citing papers by Jie Lin
This network shows the impact of papers produced by Jie Lin. 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 Jie Lin. The network helps show where Jie Lin may publish in the future.
Co-authorship network of co-authors of Jie Lin
This figure shows the co-authorship network connecting the top 25 collaborators of Jie Lin. A scholar is included among the top collaborators of Jie Lin 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 Jie Lin. Jie Lin 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 | 11 | |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 4 | |
| 8 | 7 | |
| 9 | 7 | |
| 10 | 4 | |
| 11 | 33 | |
| 12 | 9 | |
| 13 | 5 | |
| 14 | 51 | |
| 15 | 1 | |
| 16 | 4 | |
| 17 | 2 | |
| 18 | 43 | |
| 19 | On the Construction of the Entrepreneurship Education System in Colleges and Universities | 0 |
| 20 | The Definition and Strategies of Faculty′s Professional Development | 1 |
About Jie Lin
Jie Lin is a scholar working on Computational Mathematics, Media Technology and Computer Vision and Pattern Recognition, having authored 61 papers that have together received 407 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (14 papers), Advanced Image Fusion Techniques (9 papers) and Face and Expression Recognition (9 papers). The work is most often cited by research in Computational Mathematics (27 citations), Media Technology (95 citations) and Computer Vision and Pattern Recognition (179 citations). Jie Lin has collaborated with scholars based in China, United Kingdom and Taiwan. Frequent co-authors include Xi-Le Zhao, Ji Ming, Ting‐Zhu Huang, Danny Crookes, Jinghua Zhao, Chengtian Ouyang, Xiaohua Zhao, Tai-Xiang Jiang, Yong Chen and Lina Zhuang. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and Pattern Recognition.
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.