Lingling Li
- Media Technology top 0.2%
- Remote-Sensing Image Classification 68
- Advanced Image Fusion Techniques 34
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- Advanced Image and Video Retrieval Techniques 46
- Video Surveillance and Tracking Methods 25
- Advanced Neural Network Applications 17
- Artificial Intelligence top 0.5%
- Domain Adaptation and Few-Shot Learning 23
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- Remote Sensing and Land Use 21
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- Synthetic Aperture Radar (SAR) Applications and Techniques 16
- Co-authors
- Licheng JiaoFang LiuShuyuan YangXu LiuZhixi FengFan ZhangRong QuQuanlong Xu
- Journals
- IEEE Transactions on Geoscience and Remote Sensing (47 papers)IEEE Transactions on Neural Networks and Learning Systems (15 papers)IEEE Transactions on Circuits and Systems for Video Technology (13 papers)
- Partner nations
- ChinaUnited StatesMontenegro
In The Last Decade
Lingling Li
309 papers receiving 6.3k citations
Hit Papers
Peers
Comparison fields: 5 of 203
- Media Technology 1.3k
- Computer Vision and Pattern Recognition 2.0k
- Artificial Intelligence 1.4k
- Computational Theory and Mathematics 539
- Renewable Energy, Sustainability and the Environment 445
Countries citing papers authored by Lingling Li
This map shows the geographic impact of Lingling Li'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 Lingling Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lingling Li more than expected).
Fields of papers citing papers by Lingling Li
This network shows the impact of papers produced by Lingling Li. 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 Lingling Li. The network helps show where Lingling Li may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Lingling Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 4 | |
| 2 | 2025 | 6 | |
| 3 | 2025 | 2 | |
| 4 | 2025 | 4 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 7 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 9 | |
| 12 | 2023 | 37 | |
| 13 | 2023 | 4 | |
| 14 | 2023 | 1 | |
| 15 | 2023 | 1 | |
| 16 | 2023 | 7 | |
| 17 | 2022 | 10 | |
| 18 | 2022 | 26 | |
| 19 | 2018 | 11 | |
| 20 | 2015 | 1 |
About Lingling Li
Lingling Li is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 344 papers that have together received 6.5k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (68 papers), Advanced Image and Video Retrieval Techniques (46 papers), Advanced Image Fusion Techniques (34 papers), Video Surveillance and Tracking Methods (25 papers), Domain Adaptation and Few-Shot Learning (23 papers), Remote Sensing and Land Use (21 papers), Advanced Neural Network Applications (17 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (16 papers). The work is most often cited by research in Media Technology (1.3k citations), Computer Vision and Pattern Recognition (2.0k citations) and Artificial Intelligence (1.4k citations). Lingling Li has collaborated with scholars based in China, United States and Montenegro. Frequent co-authors include Licheng Jiao, Fang Liu, Shuyuan Yang, Xu Liu, Zhixi Feng, Fan Zhang, Rong Qu, Quanlong Xu, Maoguo Gong and Biao Hou. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Multimedia and Remote Sensing.
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.